**Applying to a Course: What You Need to Know**

When applying to a course at ApplyToACourse.com, many students ask if they will receive a certificate upon completion. While we are happy to provide a certificate of course completion for those who complete our program, it's essential to understand that this certificate does not necessarily guarantee success in the job market.

In fact, recruiters and hiring managers often prioritize skills over formal education or certifications. According to my own experiences interviewing hundreds of students for companies like Amazon and Yahoo Research, having a portfolio of projects showcasing your skills is much more important than any certification. I have noticed that students who are working professionals with a nice portfolio of 2-5 projects tend to be much better suited for machine learning careers than those with certificates.

The core focus of our course is not to provide a certificate at the end, but to help you transition into a machine learning career. Our job guarantee program ensures that you will receive guidance and support throughout your journey, helping you build a strong portfolio that showcases your skills. This is why we encourage all students to compare our course with other courses on the market, as there are many options available for machine learning education.

**The Value of Free Content**

One way we demonstrate our commitment to providing high-quality content is through our free videos. We offer over 14 hours of free content that covers the basics of Python, mathematical tools like linear algebra and probability statistics, as well as a few machine learning techniques like PCA and TSP. This free content allows potential students to get a taste of what our course will be like before committing to it.

We encourage all students to watch these videos and evaluate whether they feel comfortable with the material. If you find that you're able to understand most of the content after watching the free videos, then this course may be a good fit for you. Conversely, if you struggle to follow along, we want to know and can use this information to adjust our teaching methods or recommend alternative courses.

**Student Feedback**

We value your feedback and encourage all students to share their thoughts about our course. If you have any questions or concerns, please don't hesitate to reach out to us through email, phone, or social media. We respond to all inquiries as soon as possible and use student feedback to continually improve our course.

By providing a platform for open communication and continuous improvement, we aim to create the best learning experience possible for our students. Whether you're looking to transition into a machine learning career or simply want to learn more about this exciting field, we invite you to join our community and start your journey today.

**What's Next?**

If you're interested in applying to our course, we encourage you to start by exploring our free videos and content. If you have any questions or would like more information, please don't hesitate to contact us. We're always here to help and look forward to supporting you on your machine learning journey.

"WEBVTTKind: captionsLanguage: enhi folks my name is reconvert matcha Corey and I'm a co-founder at apply da course so I wanted to give you an overview of what apply to a course is about and briefly touch upon each of the core aspects of applied a a course first of all apply a course is an online machine learning and AI course and this course actually has a content of about 140 plus hours of content explaining everything in machine learning and AI and the course itself is extremely industry focused so in the course we only cover those areas of machine learning and AI which are extremely popular in the industry which are most used in the industry and we have simplified the content x2 to an extreme extent wherein we use tools like geometry we try to derive and explain each of the core concepts of whole of machine learning mathematics and AI using geometry as a basis because from our own experiences we have realized that geometry is a great tool because it's visually - because geometry is a visual tool for us to understand to grasp and to able to apply some of this machine learning and AI techniques and very importantly this course itself has no prerequisites of course some knowledge of programming is helpful but we cover everything from scratch so we use Python as a programming language of choice throughout the course and we explain Python from the basics everything from how to install Python what is a variable in Python up to state-of-the-art libraries in Python that you need for machine learning and AI in addition to Python we explain all of the basic mathematics you need we explain probability statistics linear algebra numerical optimization a little bit of calculus because some of you may have learned some of these concepts earlier in your life probably in your college days or probably in your school days but you're for many of us students forget them over a period of time so we revisit each of these concepts and all of the mathematical concepts are again taught using intuition using geometry and all of them are motivated with examples from air in machine learning and we then go on to understand basics of data analysis there we learn basic tools and methods and data analysis then we go ahead and understand all of the core techniques in a cycle machine learning so we learn supervised learning unsupervised learning techniques with matrix factorization techniques etcetera and at the end of the course we dive into one of the most state-of-the-art areas of whole of AI called deep learning wherein we dive into all of the core concepts and even state-of-the-art algorithms in deep learning and when we designed this course we wanted this course to be a great balance we want to have the right balance between theory and the practical aspects we didn't want to overdo the theory or we didn't want it to be just a coding type of course we wanted our students to be able to understand theory fairly well to whatever extent is needed of course we have skipped some proofs because they're not critical to the understanding of the algorithms at the same time we have not just made it a coding course we try to balance theory and practice so that our students at the end of the course can learn new techniques if they want to or they can solve most of the problems that they encounter in industry or in real-world situations and one of the key things that we're trying to do here is to bridge the skills gap the one of the core tenets of this course is to bridge the skills gap lot of students may already have skills they may already be developers in companies or testers in our software testers in companies or they could be working in different domains and we want to bridge the gap from their current skills we want to bridge the gap from their current skills to skills that they would need to be a successful machine learning engineer or a data scientist so if you want to know more about what all stuff is covered in our course I recommend you to go check out our website and see the detailed syllabus that we have a template a course comm frontslash course front slash applied AAA course dot a player a course online all of them with - separation so you can just go to our home page and you'll see all of this information in detail having talked about her content briefly a very very key aspect of her content is our case studies and projects so as part of the course itself we solve 15-plus real world problems and we solve each of these problems n to n by n 2 and what I mean here is we solve these problems starting with the business problem the business problem that we have to solve or the real world problem that you want to solve up to solving the whole problem including discussing how to productionize these models and that's what is very very important if you want to be a successful machine learning engineer or a data scientist some of the case studies just to give you a flavor of these case studies we actually teach you how to build a self-driving car we teach you how to how to build a cancer diagnosis system or a personalized cancer diagnosis system using using your genetic information similarly we teach you how movie recommendation happens on Netflix on YouTube etc right so these are real world problems and for each of these problems we put you in the shoes of an engineer at that company for example when we design the self-driving car we would put you in the shoes of an engineer at Tesla who has to build the system weird who has to understand the real world challenges and then design a solution similarly if you are building a movie recommendation system we put you in the shoes of an engineer at Netflix or an engineer at YouTube we has to solve these problems we just don't teach you theory we want you to be a well-rounded end-to-end machine learning engineer and data scientist so through these case studies we are trying to simulate the real world experience as closely as possible this is extremely important because just just knowing the theoretical concepts would not be sufficient in many instances what you really need is applied aspects and that's what we cover extensively throughout the course which which is which is the critical part of the course if you know all the theory but if you can't solve a real world problem end-to-end you're not ready for a career in machine learning right as part of this course we also have 30 assignments 30 mandatory assignments we also have some option assignments if you want to do them great but we have 30 mandatory assignments and these assignments are evaluated by mentors who have experienced all of whom are experienced machine learning engineers and data scientists and Industry people like me who have over a decade experience in the industry and we provide extensive feedback for each of your assignments on helping you improve your assignments because we don't want assignment to be a yes or no because in the real world you know we don't submit a yes or no solution right so whatever solutions you provide to the assignments we give you critical feedback on improving these assignments and these assignments have been designed keeping industry needs in mind these are not designed to pass an exam or to clear a test these are these are fully aligned with what you you would actually do if you join a company in a machine learning or a data science role and these assignments are learning focused they are not testing focused by which I mean we want you to learn from these assignments we want you to learn how to actually solve real-world problems as part of the assignment solution even though we teach you all of it here you have to get your hands dirty so we want this to be a learning focused exercise and we're not testing you here there is no right or wrong wrong answer there are hundreds of ways that our students have solved some of these assignments some of them brilliant obviously so these are not to test you if you're good or not these are for you to learn the ways in which you can be a successful machine learning engineer or a data scientist and these assignments have been designed again some of our students wondered if these assignments are extremely hard no but they are not trivial because if we made them trivial they will be aligned with the industry needs we made them just right so that our students can solve them with our mentorship with our content with our guidance but they are not trivial and they're not impossible hundreds of her students have solved them so you need not worry about the hardness or the impossibility of these assignments hundreds of our students who have no background where who didn't know anything well for what most of the mathematics who are not good programmers have solved this assignment successfully but putting in the effort by putting in the time by working hard so these 30 assignments are for you to learn how to solve real world problems based on all the case studies and based on all the theory all the practical aspects that we teach as part of the course okay having said that now let's go into the core structure itself right the course does not have a start date we don't have batches you can join the course at any point of time and start on your own your self-paced right we have some students who are brilliant we have some students who take slightly more time to learn and we want to respect that one of the big advantages of an online course is we have some students who watch these videos at One X speed we have some students who watch these videos at two expeed and we have some other students who take more time who actually watch some of these videos at 0.5 X speed and we have students who rewatch videos we have students who rewatch videos because all the concepts haven't sunk in the first film they watched and we encourage that right in a typical offline setting what happens is the professor or the instructor teaches you if you missed it you missed it yet everything is self-paced all you need is a decent internet connection lot of students just have a 4G connection and they've successfully watched most of our videos if we can watch YouTube videos on your smartphone or on your laptop you can watch all of our content and you can watch it from anywhere at any time you can watch it from your smartphones we have some of our students who watch it during their commute from work or from from college right when they're commuting through in public transport or in the cars when someone else is driving they watch our content and that's extremely useful because they're utilizing the time that would be wasted to learn something new so there are no batches no start date you can start at any point of time and it's fully self-paced you can learn it at whatever pace you want on whatever device you want the course itself has a 365-day or a one year editing during which time you can access all of the content you get p.m. you can access all of our mentorship all of all of the all of the stuff that we provided a credit course the content itself is very dynamic by which I mean that the course content itself keeps evolving based on feedback that we get from our students so based on feedback that we get from our students the course content itself is evolving we keep adding new content we add in different aspects of the same concept sometimes right and this has been a phenomenal right because the feedback that some of our students have provided have helped us immensely in improving our content so the content is never static it's constantly evolving to cater to the needs of our students better and a typical student that we have noticed finishes our course content in about four to five months even though the course validity itself is one year most of her students typically finish our course in four to five months if they are willing to put in 20 to 15 odds of effort per week again please note that if you are not willing to put in the effort this is not the course fun learning a completely new area or a subject like machine learning or AI is a non-trivial task right so if you're willing to put in 12 to 15 hours of effort per week you can comfortably finish this course in four to five months even if you are a below average speed learner right even if you have to watch the videos a couple of times that's okay and what we've done is a very recent stuff that we have done is for each of her students based on how many odds of effort they can put an everyday over the weekdays and weekends based on their background we give a customized and personalized schedule it's literally like a timetable it's literally like a timetable which says on so and so date these are the concepts that you should finish it's literally it's it's an extremely useful thing and in experiments that we have done with our students we notice that this customized and personalized schedule or a timetable has helped our students finish the course on time and also be very regular about doing the content like very disciplined about it and we've seen students to do content and assignments very diligently when we give them a schedule or a timetable and we customize it and personalized it to every student's needs okay having said that the next important question that we need to address is what if you are stuck someone you're watching a video you didn't understand the concept and how is that query result how is that question that you have resolved so we have multiple approaches through which we solve this because we believe that solving the students questions in a timely manner is extremely important for them to be motivated and it's also extremely it's a duty to solve these questions on time right so each video each video that you have has lots and lots and lots of comments so there is a comment section where you can leave your question so we have tens of thousands of comments already by our existing students so very likely under the video in the comment section your question is probably already answered if it is not answered feel free to leave your comment and we would answer your answer your question very very quickly we try to do it under 24 hours but very often we try to do it much faster than not ok or this this is one way because this is extremely useful because your question which is related to a question which is related to a video is asked just below that video and we can give very appropriate answers based on the video that you're watching or you can always email us at team at apply da course and we will try to get back to you as soon as possible and we are always open to talking to you on phone or Skype if that helps you resolve your questions or queries faster one of the innovations that we have done over the last few months is for a lot of student questions emails etc we actually record an audio answer but in some instances even a video answer because these questions are very good very relevant that we actually record the audio answer or the video answer and put it there I don't know of any other course which actually does this in the world to the best of my knowledge and these audio answers and video answers have been extremely useful to our students because they it's literally as if somebody is talking to them and explaining them a good answer a end to an answer or a completely completely well structured answer to their question and video answers are like terrific it's literally new content that we're creating to address student questions also we have a student interaction forum which is a Google forum that we have for all of our registered students and this is mostly for student interactions this is mostly a student student interaction this is mostly a student-student interaction forum where you can talk to other students also but any major question you have we recommend that you ask us and it's a job it's a duty and we strongly believe that we should answer all of your and address all of your queries as soon as possible of course student to student interaction forums are also very helpful because you are talking to similar minded students but we have a full-fledged very experienced team at a Friday a course to answer all of your questions to the best of our knowledge obviously a very very important aspect of applied any course is the mentorship we take our mentorship extremely seriously so as soon as you finish 50% of the course and the assignments we assign a mentor to you the mentor actually starts working with you the mentor the mentor who is actually an industry expert in machine learning in AI will start working with you trying to understand where you are coming from what type of career that you're looking at right what are your skill sets how good are you in machine learning you will start working with you on regular basis to help you build a portfolio of projects a portfolio is nothing but two to five projects two to five projects that you would do on your own with our help and mentorship right these are in addition to the 15 case studies that we've discussed here these are problems that you would solve for example if you are interested so if you are interested in internet companies then you would solve two or five problems that are typically solved by the companies like Google Facebook hammers etc or if you're interested in careers in in medicine then or if you want to join some of the pharmaceutical companies after your machine learning course you will solve two or five projects around the pharma problems or around the medicine problems right and these projects we will work very closely with you mentor you help you through building us very very strong portfolio which is extremely important for your transition into a career in machine learning right and of course we help you through the interview preparation we also help you build a strong resume based on your portfolio a portfolio is a strong proof of your skill sets this is a great way to showcase your skill sets and we help you write a blog about each of your projects build a strong github profile etcetera and all this is good but especially for experienced professionals for our students what we've just said is extreme is perfectly all right but we have a lot of experienced professionals we have professionals anywhere from one year experience to almost fifteen years of experience we have lots of professionals with five years ten years experience also for these professionals what we typically do we take extreme care of these people we take additional care of our experienced professionals because they're making a big career choice to move from their comfort zone to a completely new area so let me give you some example imagine if I'm a if if we have a student who is a experienced professional let's say with seven years or ten years of experience and let's assume the person has worked in banking and finance okay let's assume he's worked in banking and finance as a software engineer or as a software tester right either working for a banking or finance company directly like Wells Fargo or a claimed to a services company this person already has lot of domain expertise in banking and finance so we want him to build on top of the domain expertise that he or she already has there is no point ditching all of these experience that you've gained so we want to help you build on top of the seven years experience in this domain by actually working with you to build portfolio projects in and around the banking domain and our experienced professionals have to work harder right so all of your portfolio all of your portfolio will be based on your domain of expertise right and they have to work much harder than freshers because they are transitioning with lots of experience of course their compensations also will be higher so there is also a requirement and there is also an expectation of more skills from experienced professionals so in such instances we work very closely to leverage the domain expertise that these experienced professionals have and build an extremely strong portfolio extremely strong portfolio to distinguish themselves from freshers in this area right of course the amount of effort and experience and the amount of hard work that our experienced professionals need to contribute and puddin is of course more there is no denial of that fact but it is still possible for our experienced professionals to leverage and build on top of their domain expertise instead of pitching other things of course we have some experienced professionals who would say I worked in banking and finance for four ten years but I want to transition to a completely different field and work at an Internet company or an Internet start-up that's great we would certainly help you in that front but we recommend that you build on top of the expertise that you already have and once your portfolio is built once you've solved two to five projects we strongly recommend each of her students to at least two projects preferably five projects and we'll help you mentor you through that right whether you're an experienced professional or a college graduate or still studying in college right so as at the end of this we have a dedicated team which is already working with large companies and also startups which are hiring machine learning folks and we will schedule your job interviews will help you help you on tips and tricks and tools that you can leverage during your interview process we also give you career come slang we have lot of students who have had multiple offers and they're in a dilemma of what should I choose right and we we provide you that career counseling on what are the right choices for you given your current circumstances and also your current experience limit and we take our mentorship extremely seriously in addition to that a very important aspect of our course is the job guarantee or the money-back program we take this very very serious and this is a very very important aspect of our program this job guarantee or money-back is valid for all of our students who are in India and the United States we currently have a job guarantee program valid in these two geographies and the core idea is this the core idea in action is this if you finish our course if you finish our course and especially the 30 assignments at the end of 30 assignments let's assume you finish the 30 assignments on Jan 1st right you finish all of the course content and especially the assignments from the day you finish within six months which means by the end of June 30th of the same year we will get you a machine learning job and that is a promise of course let's be realistic here that sometimes we will fail right that's why we said it's not a job guarantee program it's a job guarantee your money back we will put in if you have put in the effort to finish the course and the assignments we will put in double the effort that you've put in to help you transition to a machine learning culture to help you get a machine learning job if you are interested of course we have some its students who are like I want to go pursue a master's degree of course they are free to do so but if you're interested in the machine learning job within six months of course completion so this is your course completion date and within six months we will land you in a machine learning shop in case if you fail to do so right if you fail to do so we will refund the whole course fee excluding the GST because we have already paid the GST to government of India right so we will refund the whole course feed to you if you fail to do so the reason we designed this program as part of a Friday course is because we strongly believe that student success that our students success and our success should be fully aligned we want to be successful when our students are successful and that's very very important and a core tenet of applied a a course we want to be extremely a student focused we want to help our students transition and if they have put in the effort to complete the course we feel it is a moral obligation to help them transition to a machine-learning career and if you fail I think it is our financial obligation to reform the whole course and if you're a student who is currently pursuing your undergraduate degree or a master's program we have some students when second year of bedeck third year old BTech at cetera for those students since you have not yet graduated so suppose suppose you're a second year student you finish the course you have finished the assignments within six months you haven't yet finished your degree so we can't get you a full-time job in such instances we will get you internships in startups or top companies so that your potential to get job after your graduation improves and once you finish your graduation once you graduate from your degree within six months we'll give you a full time machine level so whether you're a second year student or a third year student you can still take it don't worry don't wait for till your fourth year because if you learn if you can learn machine learning in a earlier you can do full-time internships at top companies or startups which will give you a lot of advantage in getting a full-time role especially a machine learning role on your graduation right so if you're a student don't worry the six-month course completion is something that you don't have to worry about because as soon as you finish your graduation or as soon as you are as soon as you graduate from your course within six months we will get you a machine learning job and before you even finish that will help you through internships and if you want to know more about a job guarantee all the terms very clearly please go to apply to a course comm front slash job - guarantee where we discuss the job guarantee program in lots of details and I am extremely proud to say that tenly in the last 11 months of our operation we have had 100% success rate of all the students will finish their course in assignments every one of them has got placed in under six months both in India and the United States and very fun many of our students actually have had multiple offers that's where our Career Counseling comes into play and we have we helped some of our students make the right choices on where they should go so if you I also recommend you to check out our success stories on our website so you can go to airplane a course.com front slash sucks or siphon stories which is a partial list of some of our students who've got placed at applied AAA course we have students we've gotten placed in companies like Ernst & Young Samsung Qualcomm Zoho Intel in the u.s. General Electric visa startups like Aria dot AI and also very interesting ecommerce company in Japan called ricotta in Japan and we have a wide spectrum of students we have students from top-notch universities in the world we have from really really top-notch universities both in India in the United States we have students from very very small engineering colleges we have we have working professionals from top-notch companies like Google Facebook Amazon to employees working in small services companies right we have a wide spectrum of audience and our success stories reflect that fact and if you want a better company if you want to land a job in a better company you have to work hard and build a stronger portfolio the stronger the portfolio you build the better would be the job you would get we have had we have had people from small engineering colleges we have gotten top-notch offers in top-notch product based companies right so the ball is in your court if you're willing to put in the effort we are here to help you mentor you solve all of your queries and transition you to a machine-learning come here so please check out all of our success stories which is still a partial list at everybody a course.com front slash success stories having said that some of our students ask us if is a course completion certificate of course we'll give you a course completion certificate from apply to a course but let me be very frank with you okay because I have done hundreds of interviews for companies like Amazon both in India and the US and also for Yahoo research right so every resume that I bought at Amazon would have some certificate some course completion certificate from from from all of the major online courses right or from top universities like Stanford but typically recruiters hiring managers in the industry do not look at these certificates it really doesn't matter it's an unfortunate fact but again this is all from my own experiences the course completion certificates at most online or offline machine learning courses do not matter what matters is the skills that you have and you can showcase your skills through the portfolio of projects through the portfolio of projects that we help you build from my own experience of interviewing hundreds of students I have noticed that those students are working professionals who have a nice portfolio of at least two to five projects two to five projects or case studies that they have solved with detailed code lots of plots detailed description about the models nice blogs they tend to be much much better than people who have certificates this is my own personal experience of interviewing hundreds of folks both named both in India and the United States for amazon.com right so while we give you a certificate because our students ask us to certificates do not matter for transitioning to a machine learning it is your skills that matter and certificates do not guarantee skills your portfolio which you build is what help will help you transition to a machine learning career because this shows that your skills and you can solve real-world machine learning problems and the core focus of her goal of core focus of her whole course is not a certificate at the end of it it is to help you transition to a machine learning career that's the core focus that's when we have the job guarantee program first place right so extremely important aspect is we want you to check out some of our sample and free videos you can just go to our apply to a course comm home page and you will see a link to free videos we have we have close to 14 or 15 hours of content which is free wherein we cover everything from basics of Python a bunch of mathematical tools like linear algebra probability statistics we also cover a couple of machine learning techniques like PCA and TSP all this is free of cost because we want our students to learn what to learn the way we teach we want them to sample us we want them to see how we teach before they even jump into the full course before the register for the course we want them to see what our course will look like and this is a great tool for us for our students to self evaluate themselves we don't want to have a test to join the course we want our students to go through this 14 15 hours of free content see if they're able to understand the content if they are not able to understand the content this is not the right course for them I'm being very frank with you but if you are able to understand this free content right maybe you have to watch twice for some videos that's okay but at the end of it if you are able to watch these videos and understand most of the content then this course is the right course for you very importantly there are lots of courses out there both online and offline for machine learning we strongly encourage all of our students to compare our course with other courses because if I'm a consumer right if I'm a customer that's what I would do when I'm buying a refrigerator I look at tens of refrigerators before I buy and this is a career chart this is this is a career choice that I'm making so I want to have the best instructors the best mentorship the best query resolution all of that so please compare us with other courses and choose the one that best suits you we strongly encourage your students to do that and any feedback you have about the course please send it to us just please email us your feedback at team a template equals because it is through students feedback or potential students feedback if we constantly improve our course so this video this 30 odd minutes video is an overview of everything that we do at applied a a course broadly speaking of course there are some aspects that I missed here and there but this is a broad overview I hope this gives you a fair idea about what applied a a course is about and any questions you have you can just go to apply to a course comm we have a number phone numbers there you can call them and we try to respond to you as soon as possible or you can email us obviously we have all the standard channels on Facebook Google please reach out to us and we will try to resolve any questions you have about the course as soon as possiblehi folks my name is reconvert matcha Corey and I'm a co-founder at apply da course so I wanted to give you an overview of what apply to a course is about and briefly touch upon each of the core aspects of applied a a course first of all apply a course is an online machine learning and AI course and this course actually has a content of about 140 plus hours of content explaining everything in machine learning and AI and the course itself is extremely industry focused so in the course we only cover those areas of machine learning and AI which are extremely popular in the industry which are most used in the industry and we have simplified the content x2 to an extreme extent wherein we use tools like geometry we try to derive and explain each of the core concepts of whole of machine learning mathematics and AI using geometry as a basis because from our own experiences we have realized that geometry is a great tool because it's visually - because geometry is a visual tool for us to understand to grasp and to able to apply some of this machine learning and AI techniques and very importantly this course itself has no prerequisites of course some knowledge of programming is helpful but we cover everything from scratch so we use Python as a programming language of choice throughout the course and we explain Python from the basics everything from how to install Python what is a variable in Python up to state-of-the-art libraries in Python that you need for machine learning and AI in addition to Python we explain all of the basic mathematics you need we explain probability statistics linear algebra numerical optimization a little bit of calculus because some of you may have learned some of these concepts earlier in your life probably in your college days or probably in your school days but you're for many of us students forget them over a period of time so we revisit each of these concepts and all of the mathematical concepts are again taught using intuition using geometry and all of them are motivated with examples from air in machine learning and we then go on to understand basics of data analysis there we learn basic tools and methods and data analysis then we go ahead and understand all of the core techniques in a cycle machine learning so we learn supervised learning unsupervised learning techniques with matrix factorization techniques etcetera and at the end of the course we dive into one of the most state-of-the-art areas of whole of AI called deep learning wherein we dive into all of the core concepts and even state-of-the-art algorithms in deep learning and when we designed this course we wanted this course to be a great balance we want to have the right balance between theory and the practical aspects we didn't want to overdo the theory or we didn't want it to be just a coding type of course we wanted our students to be able to understand theory fairly well to whatever extent is needed of course we have skipped some proofs because they're not critical to the understanding of the algorithms at the same time we have not just made it a coding course we try to balance theory and practice so that our students at the end of the course can learn new techniques if they want to or they can solve most of the problems that they encounter in industry or in real-world situations and one of the key things that we're trying to do here is to bridge the skills gap the one of the core tenets of this course is to bridge the skills gap lot of students may already have skills they may already be developers in companies or testers in our software testers in companies or they could be working in different domains and we want to bridge the gap from their current skills we want to bridge the gap from their current skills to skills that they would need to be a successful machine learning engineer or a data scientist so if you want to know more about what all stuff is covered in our course I recommend you to go check out our website and see the detailed syllabus that we have a template a course comm frontslash course front slash applied AAA course dot a player a course online all of them with - separation so you can just go to our home page and you'll see all of this information in detail having talked about her content briefly a very very key aspect of her content is our case studies and projects so as part of the course itself we solve 15-plus real world problems and we solve each of these problems n to n by n 2 and what I mean here is we solve these problems starting with the business problem the business problem that we have to solve or the real world problem that you want to solve up to solving the whole problem including discussing how to productionize these models and that's what is very very important if you want to be a successful machine learning engineer or a data scientist some of the case studies just to give you a flavor of these case studies we actually teach you how to build a self-driving car we teach you how to how to build a cancer diagnosis system or a personalized cancer diagnosis system using using your genetic information similarly we teach you how movie recommendation happens on Netflix on YouTube etc right so these are real world problems and for each of these problems we put you in the shoes of an engineer at that company for example when we design the self-driving car we would put you in the shoes of an engineer at Tesla who has to build the system weird who has to understand the real world challenges and then design a solution similarly if you are building a movie recommendation system we put you in the shoes of an engineer at Netflix or an engineer at YouTube we has to solve these problems we just don't teach you theory we want you to be a well-rounded end-to-end machine learning engineer and data scientist so through these case studies we are trying to simulate the real world experience as closely as possible this is extremely important because just just knowing the theoretical concepts would not be sufficient in many instances what you really need is applied aspects and that's what we cover extensively throughout the course which which is which is the critical part of the course if you know all the theory but if you can't solve a real world problem end-to-end you're not ready for a career in machine learning right as part of this course we also have 30 assignments 30 mandatory assignments we also have some option assignments if you want to do them great but we have 30 mandatory assignments and these assignments are evaluated by mentors who have experienced all of whom are experienced machine learning engineers and data scientists and Industry people like me who have over a decade experience in the industry and we provide extensive feedback for each of your assignments on helping you improve your assignments because we don't want assignment to be a yes or no because in the real world you know we don't submit a yes or no solution right so whatever solutions you provide to the assignments we give you critical feedback on improving these assignments and these assignments have been designed keeping industry needs in mind these are not designed to pass an exam or to clear a test these are these are fully aligned with what you you would actually do if you join a company in a machine learning or a data science role and these assignments are learning focused they are not testing focused by which I mean we want you to learn from these assignments we want you to learn how to actually solve real-world problems as part of the assignment solution even though we teach you all of it here you have to get your hands dirty so we want this to be a learning focused exercise and we're not testing you here there is no right or wrong wrong answer there are hundreds of ways that our students have solved some of these assignments some of them brilliant obviously so these are not to test you if you're good or not these are for you to learn the ways in which you can be a successful machine learning engineer or a data scientist and these assignments have been designed again some of our students wondered if these assignments are extremely hard no but they are not trivial because if we made them trivial they will be aligned with the industry needs we made them just right so that our students can solve them with our mentorship with our content with our guidance but they are not trivial and they're not impossible hundreds of her students have solved them so you need not worry about the hardness or the impossibility of these assignments hundreds of our students who have no background where who didn't know anything well for what most of the mathematics who are not good programmers have solved this assignment successfully but putting in the effort by putting in the time by working hard so these 30 assignments are for you to learn how to solve real world problems based on all the case studies and based on all the theory all the practical aspects that we teach as part of the course okay having said that now let's go into the core structure itself right the course does not have a start date we don't have batches you can join the course at any point of time and start on your own your self-paced right we have some students who are brilliant we have some students who take slightly more time to learn and we want to respect that one of the big advantages of an online course is we have some students who watch these videos at One X speed we have some students who watch these videos at two expeed and we have some other students who take more time who actually watch some of these videos at 0.5 X speed and we have students who rewatch videos we have students who rewatch videos because all the concepts haven't sunk in the first film they watched and we encourage that right in a typical offline setting what happens is the professor or the instructor teaches you if you missed it you missed it yet everything is self-paced all you need is a decent internet connection lot of students just have a 4G connection and they've successfully watched most of our videos if we can watch YouTube videos on your smartphone or on your laptop you can watch all of our content and you can watch it from anywhere at any time you can watch it from your smartphones we have some of our students who watch it during their commute from work or from from college right when they're commuting through in public transport or in the cars when someone else is driving they watch our content and that's extremely useful because they're utilizing the time that would be wasted to learn something new so there are no batches no start date you can start at any point of time and it's fully self-paced you can learn it at whatever pace you want on whatever device you want the course itself has a 365-day or a one year editing during which time you can access all of the content you get p.m. you can access all of our mentorship all of all of the all of the stuff that we provided a credit course the content itself is very dynamic by which I mean that the course content itself keeps evolving based on feedback that we get from our students so based on feedback that we get from our students the course content itself is evolving we keep adding new content we add in different aspects of the same concept sometimes right and this has been a phenomenal right because the feedback that some of our students have provided have helped us immensely in improving our content so the content is never static it's constantly evolving to cater to the needs of our students better and a typical student that we have noticed finishes our course content in about four to five months even though the course validity itself is one year most of her students typically finish our course in four to five months if they are willing to put in 20 to 15 odds of effort per week again please note that if you are not willing to put in the effort this is not the course fun learning a completely new area or a subject like machine learning or AI is a non-trivial task right so if you're willing to put in 12 to 15 hours of effort per week you can comfortably finish this course in four to five months even if you are a below average speed learner right even if you have to watch the videos a couple of times that's okay and what we've done is a very recent stuff that we have done is for each of her students based on how many odds of effort they can put an everyday over the weekdays and weekends based on their background we give a customized and personalized schedule it's literally like a timetable it's literally like a timetable which says on so and so date these are the concepts that you should finish it's literally it's it's an extremely useful thing and in experiments that we have done with our students we notice that this customized and personalized schedule or a timetable has helped our students finish the course on time and also be very regular about doing the content like very disciplined about it and we've seen students to do content and assignments very diligently when we give them a schedule or a timetable and we customize it and personalized it to every student's needs okay having said that the next important question that we need to address is what if you are stuck someone you're watching a video you didn't understand the concept and how is that query result how is that question that you have resolved so we have multiple approaches through which we solve this because we believe that solving the students questions in a timely manner is extremely important for them to be motivated and it's also extremely it's a duty to solve these questions on time right so each video each video that you have has lots and lots and lots of comments so there is a comment section where you can leave your question so we have tens of thousands of comments already by our existing students so very likely under the video in the comment section your question is probably already answered if it is not answered feel free to leave your comment and we would answer your answer your question very very quickly we try to do it under 24 hours but very often we try to do it much faster than not ok or this this is one way because this is extremely useful because your question which is related to a question which is related to a video is asked just below that video and we can give very appropriate answers based on the video that you're watching or you can always email us at team at apply da course and we will try to get back to you as soon as possible and we are always open to talking to you on phone or Skype if that helps you resolve your questions or queries faster one of the innovations that we have done over the last few months is for a lot of student questions emails etc we actually record an audio answer but in some instances even a video answer because these questions are very good very relevant that we actually record the audio answer or the video answer and put it there I don't know of any other course which actually does this in the world to the best of my knowledge and these audio answers and video answers have been extremely useful to our students because they it's literally as if somebody is talking to them and explaining them a good answer a end to an answer or a completely completely well structured answer to their question and video answers are like terrific it's literally new content that we're creating to address student questions also we have a student interaction forum which is a Google forum that we have for all of our registered students and this is mostly for student interactions this is mostly a student student interaction this is mostly a student-student interaction forum where you can talk to other students also but any major question you have we recommend that you ask us and it's a job it's a duty and we strongly believe that we should answer all of your and address all of your queries as soon as possible of course student to student interaction forums are also very helpful because you are talking to similar minded students but we have a full-fledged very experienced team at a Friday a course to answer all of your questions to the best of our knowledge obviously a very very important aspect of applied any course is the mentorship we take our mentorship extremely seriously so as soon as you finish 50% of the course and the assignments we assign a mentor to you the mentor actually starts working with you the mentor the mentor who is actually an industry expert in machine learning in AI will start working with you trying to understand where you are coming from what type of career that you're looking at right what are your skill sets how good are you in machine learning you will start working with you on regular basis to help you build a portfolio of projects a portfolio is nothing but two to five projects two to five projects that you would do on your own with our help and mentorship right these are in addition to the 15 case studies that we've discussed here these are problems that you would solve for example if you are interested so if you are interested in internet companies then you would solve two or five problems that are typically solved by the companies like Google Facebook hammers etc or if you're interested in careers in in medicine then or if you want to join some of the pharmaceutical companies after your machine learning course you will solve two or five projects around the pharma problems or around the medicine problems right and these projects we will work very closely with you mentor you help you through building us very very strong portfolio which is extremely important for your transition into a career in machine learning right and of course we help you through the interview preparation we also help you build a strong resume based on your portfolio a portfolio is a strong proof of your skill sets this is a great way to showcase your skill sets and we help you write a blog about each of your projects build a strong github profile etcetera and all this is good but especially for experienced professionals for our students what we've just said is extreme is perfectly all right but we have a lot of experienced professionals we have professionals anywhere from one year experience to almost fifteen years of experience we have lots of professionals with five years ten years experience also for these professionals what we typically do we take extreme care of these people we take additional care of our experienced professionals because they're making a big career choice to move from their comfort zone to a completely new area so let me give you some example imagine if I'm a if if we have a student who is a experienced professional let's say with seven years or ten years of experience and let's assume the person has worked in banking and finance okay let's assume he's worked in banking and finance as a software engineer or as a software tester right either working for a banking or finance company directly like Wells Fargo or a claimed to a services company this person already has lot of domain expertise in banking and finance so we want him to build on top of the domain expertise that he or she already has there is no point ditching all of these experience that you've gained so we want to help you build on top of the seven years experience in this domain by actually working with you to build portfolio projects in and around the banking domain and our experienced professionals have to work harder right so all of your portfolio all of your portfolio will be based on your domain of expertise right and they have to work much harder than freshers because they are transitioning with lots of experience of course their compensations also will be higher so there is also a requirement and there is also an expectation of more skills from experienced professionals so in such instances we work very closely to leverage the domain expertise that these experienced professionals have and build an extremely strong portfolio extremely strong portfolio to distinguish themselves from freshers in this area right of course the amount of effort and experience and the amount of hard work that our experienced professionals need to contribute and puddin is of course more there is no denial of that fact but it is still possible for our experienced professionals to leverage and build on top of their domain expertise instead of pitching other things of course we have some experienced professionals who would say I worked in banking and finance for four ten years but I want to transition to a completely different field and work at an Internet company or an Internet start-up that's great we would certainly help you in that front but we recommend that you build on top of the expertise that you already have and once your portfolio is built once you've solved two to five projects we strongly recommend each of her students to at least two projects preferably five projects and we'll help you mentor you through that right whether you're an experienced professional or a college graduate or still studying in college right so as at the end of this we have a dedicated team which is already working with large companies and also startups which are hiring machine learning folks and we will schedule your job interviews will help you help you on tips and tricks and tools that you can leverage during your interview process we also give you career come slang we have lot of students who have had multiple offers and they're in a dilemma of what should I choose right and we we provide you that career counseling on what are the right choices for you given your current circumstances and also your current experience limit and we take our mentorship extremely seriously in addition to that a very important aspect of our course is the job guarantee or the money-back program we take this very very serious and this is a very very important aspect of our program this job guarantee or money-back is valid for all of our students who are in India and the United States we currently have a job guarantee program valid in these two geographies and the core idea is this the core idea in action is this if you finish our course if you finish our course and especially the 30 assignments at the end of 30 assignments let's assume you finish the 30 assignments on Jan 1st right you finish all of the course content and especially the assignments from the day you finish within six months which means by the end of June 30th of the same year we will get you a machine learning job and that is a promise of course let's be realistic here that sometimes we will fail right that's why we said it's not a job guarantee program it's a job guarantee your money back we will put in if you have put in the effort to finish the course and the assignments we will put in double the effort that you've put in to help you transition to a machine learning culture to help you get a machine learning job if you are interested of course we have some its students who are like I want to go pursue a master's degree of course they are free to do so but if you're interested in the machine learning job within six months of course completion so this is your course completion date and within six months we will land you in a machine learning shop in case if you fail to do so right if you fail to do so we will refund the whole course fee excluding the GST because we have already paid the GST to government of India right so we will refund the whole course feed to you if you fail to do so the reason we designed this program as part of a Friday course is because we strongly believe that student success that our students success and our success should be fully aligned we want to be successful when our students are successful and that's very very important and a core tenet of applied a a course we want to be extremely a student focused we want to help our students transition and if they have put in the effort to complete the course we feel it is a moral obligation to help them transition to a machine-learning career and if you fail I think it is our financial obligation to reform the whole course and if you're a student who is currently pursuing your undergraduate degree or a master's program we have some students when second year of bedeck third year old BTech at cetera for those students since you have not yet graduated so suppose suppose you're a second year student you finish the course you have finished the assignments within six months you haven't yet finished your degree so we can't get you a full-time job in such instances we will get you internships in startups or top companies so that your potential to get job after your graduation improves and once you finish your graduation once you graduate from your degree within six months we'll give you a full time machine level so whether you're a second year student or a third year student you can still take it don't worry don't wait for till your fourth year because if you learn if you can learn machine learning in a earlier you can do full-time internships at top companies or startups which will give you a lot of advantage in getting a full-time role especially a machine learning role on your graduation right so if you're a student don't worry the six-month course completion is something that you don't have to worry about because as soon as you finish your graduation or as soon as you are as soon as you graduate from your course within six months we will get you a machine learning job and before you even finish that will help you through internships and if you want to know more about a job guarantee all the terms very clearly please go to apply to a course comm front slash job - guarantee where we discuss the job guarantee program in lots of details and I am extremely proud to say that tenly in the last 11 months of our operation we have had 100% success rate of all the students will finish their course in assignments every one of them has got placed in under six months both in India and the United States and very fun many of our students actually have had multiple offers that's where our Career Counseling comes into play and we have we helped some of our students make the right choices on where they should go so if you I also recommend you to check out our success stories on our website so you can go to airplane a course.com front slash sucks or siphon stories which is a partial list of some of our students who've got placed at applied AAA course we have students we've gotten placed in companies like Ernst & Young Samsung Qualcomm Zoho Intel in the u.s. General Electric visa startups like Aria dot AI and also very interesting ecommerce company in Japan called ricotta in Japan and we have a wide spectrum of students we have students from top-notch universities in the world we have from really really top-notch universities both in India in the United States we have students from very very small engineering colleges we have we have working professionals from top-notch companies like Google Facebook Amazon to employees working in small services companies right we have a wide spectrum of audience and our success stories reflect that fact and if you want a better company if you want to land a job in a better company you have to work hard and build a stronger portfolio the stronger the portfolio you build the better would be the job you would get we have had we have had people from small engineering colleges we have gotten top-notch offers in top-notch product based companies right so the ball is in your court if you're willing to put in the effort we are here to help you mentor you solve all of your queries and transition you to a machine-learning come here so please check out all of our success stories which is still a partial list at everybody a course.com front slash success stories having said that some of our students ask us if is a course completion certificate of course we'll give you a course completion certificate from apply to a course but let me be very frank with you okay because I have done hundreds of interviews for companies like Amazon both in India and the US and also for Yahoo research right so every resume that I bought at Amazon would have some certificate some course completion certificate from from from all of the major online courses right or from top universities like Stanford but typically recruiters hiring managers in the industry do not look at these certificates it really doesn't matter it's an unfortunate fact but again this is all from my own experiences the course completion certificates at most online or offline machine learning courses do not matter what matters is the skills that you have and you can showcase your skills through the portfolio of projects through the portfolio of projects that we help you build from my own experience of interviewing hundreds of students I have noticed that those students are working professionals who have a nice portfolio of at least two to five projects two to five projects or case studies that they have solved with detailed code lots of plots detailed description about the models nice blogs they tend to be much much better than people who have certificates this is my own personal experience of interviewing hundreds of folks both named both in India and the United States for amazon.com right so while we give you a certificate because our students ask us to certificates do not matter for transitioning to a machine learning it is your skills that matter and certificates do not guarantee skills your portfolio which you build is what help will help you transition to a machine learning career because this shows that your skills and you can solve real-world machine learning problems and the core focus of her goal of core focus of her whole course is not a certificate at the end of it it is to help you transition to a machine learning career that's the core focus that's when we have the job guarantee program first place right so extremely important aspect is we want you to check out some of our sample and free videos you can just go to our apply to a course comm home page and you will see a link to free videos we have we have close to 14 or 15 hours of content which is free wherein we cover everything from basics of Python a bunch of mathematical tools like linear algebra probability statistics we also cover a couple of machine learning techniques like PCA and TSP all this is free of cost because we want our students to learn what to learn the way we teach we want them to sample us we want them to see how we teach before they even jump into the full course before the register for the course we want them to see what our course will look like and this is a great tool for us for our students to self evaluate themselves we don't want to have a test to join the course we want our students to go through this 14 15 hours of free content see if they're able to understand the content if they are not able to understand the content this is not the right course for them I'm being very frank with you but if you are able to understand this free content right maybe you have to watch twice for some videos that's okay but at the end of it if you are able to watch these videos and understand most of the content then this course is the right course for you very importantly there are lots of courses out there both online and offline for machine learning we strongly encourage all of our students to compare our course with other courses because if I'm a consumer right if I'm a customer that's what I would do when I'm buying a refrigerator I look at tens of refrigerators before I buy and this is a career chart this is this is a career choice that I'm making so I want to have the best instructors the best mentorship the best query resolution all of that so please compare us with other courses and choose the one that best suits you we strongly encourage your students to do that and any feedback you have about the course please send it to us just please email us your feedback at team a template equals because it is through students feedback or potential students feedback if we constantly improve our course so this video this 30 odd minutes video is an overview of everything that we do at applied a a course broadly speaking of course there are some aspects that I missed here and there but this is a broad overview I hope this gives you a fair idea about what applied a a course is about and any questions you have you can just go to apply to a course comm we have a number phone numbers there you can call them and we try to respond to you as soon as possible or you can email us obviously we have all the standard channels on Facebook Google please reach out to us and we will try to resolve any questions you have about the course as soon as possible\n"