Quora is basically a repository of questions and answers. Imagine there are two questions out there which are exactly the same. It makes sense for Quora to group both of these questions so that all the answers are shared between these two questions. Right it's a problem that Quora actually solves in the real world.

We also have some data set that Quora has publicly open source and provided for everybody to access. We actually take the data sets to use techniques in natural language processing and text understanding to solve this problem. Similarly, Uber has given us data about how many taxi pickups or how many cap pickups happen at a given location at a given time over multiple years in New York City. We use the data to build a first cut solution on predicting how many pickups will happen at a given location at a given time.

It's it's a phenomenal problem to solve. It's a massive amount of data set that we have to crunch through and understand what's happening. All of these problems are solved at an internal level rigor. We do not want to water down the rigor or the depth at which these problems are sorted. We are based on our experience in product-based companies. We want it we want these problems to be solved the way a typical intern at a tier one product-based company would solve over a three to six month period.

We do not want to water down the rigor or the other depth of solving the problem. We want you to feel it more like an internship like an unpaid internship. Unfortunately, we can't pay you back for this. You have to pay us for this area codes for this project. So, this is like getting a real-world experience of how AI problems are solved in the real world.

In addition to all of this, we provide phenomenal customer service. We have five engineers from top-notch institutions with phenomenal work experience who will help you through solving your project end-to-end. If you're stuck at a code snippet if you don't understand the code snippet, we have our engineers always ready to help you. And we try to answer all of our questions within 24 hours to the best of her ability. Sometimes we may miss it here and there but we try to do it to the best of our ability.

Most importantly, there are no prerequisites for this project. We expect you to have some familiarity with the programming language like C++, or Java, and we do all of this in Python because python has terrific libraries for machine learning AI and data science. So, we actually use Python. For those of you who don't know Python, please don't worry. We have tens of hours of video content explaining the basics of Python. Everything from what a variable is to understanding all of these very interesting libraries called matplotlib and scikit-learn which are used for machine learning.

For each of the problems that we have, we have a five to ten-minute description on what the problem is and what we're trying to solve. So, then you get a flavor of problems that we that we are solving. And you can pick any one problem that you want to solve as part of your undergraduate or graduate project. Right. Most of these concepts are explained extremely simply. Even very very complex mathematical ideas are actually explained very simply.

I want you to test it out. I want you folks to go check out our video content. It was fun building all of this content, and I want you to see how some of these Concepts can be simplified. And of course, we'll always here to uh get your feedback improve some of the videos again. Nothing in this video content is static if you see a lot of people saying that okay I didn't understand this specific concept that we explained this way we go back and redo that video it's okay it's perfectly okay for us to do it because we want our students to be successful at the end of their course getting a flavor of what a real-world AI problem solution is like. That's the key goal here.

We want undergraduate and graduate students who are just going into the job market understand what actually solving your AI or what solving a real-world problem looks like this will give you a flavor. We have another course called Applied A Quartz.com which is much more broad. Which is typically targeted towards students who want to go and get an A job at the end of their undergraduate or graduate school. This is more about doing a project getting a flavor of what things are in the real world, and it will be fun.

I hope I hope you love some of this content. And we're always here to hear your feedback.

"WEBVTTKind: captionsLanguage: enare other very important codes is called applied a project or case study this is typically targeted towards undergraduate and graduate students typically students in the third year or fourth year of undergrad or first or second year of grad school like Masters or pursuing Masters typically in grad school and pursuing undergraduate bachelor's degree in underground who want to do an AI project at the end of the coursework or during their coursework and we believe that there is enormous amount of potential in this undergraduate and graduate students it's just that they don't have the right mentorship and right content to do a great project uh towards this project we give you 100 plus hours of video content explaining you from everything from what is what is uh what is gaussian distribution what is conditional probability uh what is what is a histogram what is a PDF what is a CDF up to all the techniques that to learn to solve your problem at hand right unlike other other agencies or other institutions that give that help you build projects we want to help you do it the right way which is learn the whole concept learn all the nuances of the concept and as you are learning it solve the real world problem and we believe that people can people can do this whole course over a three to six month period so that it fits into the final year project that most undergrad and grad students typically do so during this while you're doing this project we actually pick a real world problem and real world data sets for example we pick up Facebook's friend graph which is basically a graph where your vertices are people your Edge is basically if two if two people are connected or if two people are friends you have an edge we actually have some data set from companies like Facebook who provide this data uh thankfully um they've made this data publicly available to everybody and we use actual real world data sets to build a first cut solution so what we do is we go from raw data do all the basic data analysis called exploratory data analysis and we go and build multiple models we do not teach you one algorithm on how to solve it we solve the whole problem using multiple algorithms and help you pick the right algorithm and this this whole process goes from explaining to the basics to helping you solve the problem end to end and we also provide all the research papers and all the recent research work which is relevant to solving that problem to give you a flavor of some of our problems we have the Facebook friend recommendation problem which I just explained you available we also have another problem called quora question similarity as you all might already know quora is basically a repository of questions and answers imagine there are two questions out there which are exactly the same right it makes sense for quora to group both of these questions so that all the answers are are shared between these two questions right so it's a problem that quora actually solves in the real world and we also have some data set that quora has publicly open source and provided for everybody to access and we actually take the data sets to use techniques in nature language processing and text understanding to solve this problem similarly Uber has given us data about how many taxi pickups or how many cap pickups happen at a given location at a given time over multiple Years in New York City and we use the data to build a first cut Solution on predicting how many pickups will happen at a given location at a given time it's it's a phenomenal problem to solve it's a massive amount of data set that we have to crunch through and understand what's happening and all of these problems are solved at an internal level rigor we do not want to water down the rigor or the or the depth at which these problems are sorted we are we are based on our experience in product based companies we want it we want these problems to be solved the way a typical intern at a tier one product based company would solve over a three to six month period we do not want to water down the rigor or the other depth of solving the problem we want you to feel it more like an internship like an unpaid internship unfortunately we can't pay you back for this you have to pay us for this area codes for this project so this is like this is like getting a real world experience of how AI problems are solved in the real world in addition to all of this we provide phenomenal customer service we have five Engineers from top-notch institutions with phenomenal work experience who will help you through solving your project end to end if you're stuck at a code snippet if you don't understand the code snippet we have our Engineers always ready to help you and we try to answer all of our questions within 24 hours to the best of her ability sometimes we may miss it here and there but we try to do it to the best of our ability and most importantly there are no prerequisites for this for for doing this project we expect we have some familiarity with the programming language like C C plus plus or Java and we do all of this in Python because python has terrific libraries for machine learning Ai and data science so we actually use Python and for those of you who don't know python please don't worry we have tens of hours of video content explaining the basics of python everything from what a variable is to understanding all of this very interesting libraries called matplotlab and scikit-learn which are used for machine learning and I strongly recommend you to visit our site applied a course and watch out our free videos which are publicly available for everyone for each of the problems that we have we have we have a five to ten minute description on what the problem is and what we're trying to solve so then you get a flavor of problems that we that we are solving and you can pick any one problem that you want to solve as part of your undergraduate or graduate project right and most of these concepts are explained extremely simply even very very complex mathematical ideas are actually explained very simply I want you to test it out I want you folks to go check out our video content it was fun building all of this content and I want you to see how how some of these Concepts can be simplified and of course we'll always here to uh get your feedback improve some of the videos again nothing in this video content is static if you see a lot of people saying that okay I didn't understand this specific concept that we explained this way we go back and redo that video it's okay it's perfectly okay for us to do it because we want our students to be successful at the end of their course getting a flavor of what a real world AI problem solution is like that that's the key goal here we want undergraduate and graduate students who are just going into the job market understand what actually solving your AI or what solving a real world a problem looks like this will give you a flavor we have another course called applied a quartz.com which is much more broad which is which is typically targeted towards students who want to go and get an a job at the end of their undergraduate or graduate school this is more about doing a project getting a flavor of what what how things are in the real world and it will be fun I hope I hope you love some of this content and we're always here to hear your feedback and hope to see you in the applied a project courseare other very important codes is called applied a project or case study this is typically targeted towards undergraduate and graduate students typically students in the third year or fourth year of undergrad or first or second year of grad school like Masters or pursuing Masters typically in grad school and pursuing undergraduate bachelor's degree in underground who want to do an AI project at the end of the coursework or during their coursework and we believe that there is enormous amount of potential in this undergraduate and graduate students it's just that they don't have the right mentorship and right content to do a great project uh towards this project we give you 100 plus hours of video content explaining you from everything from what is what is uh what is gaussian distribution what is conditional probability uh what is what is a histogram what is a PDF what is a CDF up to all the techniques that to learn to solve your problem at hand right unlike other other agencies or other institutions that give that help you build projects we want to help you do it the right way which is learn the whole concept learn all the nuances of the concept and as you are learning it solve the real world problem and we believe that people can people can do this whole course over a three to six month period so that it fits into the final year project that most undergrad and grad students typically do so during this while you're doing this project we actually pick a real world problem and real world data sets for example we pick up Facebook's friend graph which is basically a graph where your vertices are people your Edge is basically if two if two people are connected or if two people are friends you have an edge we actually have some data set from companies like Facebook who provide this data uh thankfully um they've made this data publicly available to everybody and we use actual real world data sets to build a first cut solution so what we do is we go from raw data do all the basic data analysis called exploratory data analysis and we go and build multiple models we do not teach you one algorithm on how to solve it we solve the whole problem using multiple algorithms and help you pick the right algorithm and this this whole process goes from explaining to the basics to helping you solve the problem end to end and we also provide all the research papers and all the recent research work which is relevant to solving that problem to give you a flavor of some of our problems we have the Facebook friend recommendation problem which I just explained you available we also have another problem called quora question similarity as you all might already know quora is basically a repository of questions and answers imagine there are two questions out there which are exactly the same right it makes sense for quora to group both of these questions so that all the answers are are shared between these two questions right so it's a problem that quora actually solves in the real world and we also have some data set that quora has publicly open source and provided for everybody to access and we actually take the data sets to use techniques in nature language processing and text understanding to solve this problem similarly Uber has given us data about how many taxi pickups or how many cap pickups happen at a given location at a given time over multiple Years in New York City and we use the data to build a first cut Solution on predicting how many pickups will happen at a given location at a given time it's it's a phenomenal problem to solve it's a massive amount of data set that we have to crunch through and understand what's happening and all of these problems are solved at an internal level rigor we do not want to water down the rigor or the or the depth at which these problems are sorted we are we are based on our experience in product based companies we want it we want these problems to be solved the way a typical intern at a tier one product based company would solve over a three to six month period we do not want to water down the rigor or the other depth of solving the problem we want you to feel it more like an internship like an unpaid internship unfortunately we can't pay you back for this you have to pay us for this area codes for this project so this is like this is like getting a real world experience of how AI problems are solved in the real world in addition to all of this we provide phenomenal customer service we have five Engineers from top-notch institutions with phenomenal work experience who will help you through solving your project end to end if you're stuck at a code snippet if you don't understand the code snippet we have our Engineers always ready to help you and we try to answer all of our questions within 24 hours to the best of her ability sometimes we may miss it here and there but we try to do it to the best of our ability and most importantly there are no prerequisites for this for for doing this project we expect we have some familiarity with the programming language like C C plus plus or Java and we do all of this in Python because python has terrific libraries for machine learning Ai and data science so we actually use Python and for those of you who don't know python please don't worry we have tens of hours of video content explaining the basics of python everything from what a variable is to understanding all of this very interesting libraries called matplotlab and scikit-learn which are used for machine learning and I strongly recommend you to visit our site applied a course and watch out our free videos which are publicly available for everyone for each of the problems that we have we have we have a five to ten minute description on what the problem is and what we're trying to solve so then you get a flavor of problems that we that we are solving and you can pick any one problem that you want to solve as part of your undergraduate or graduate project right and most of these concepts are explained extremely simply even very very complex mathematical ideas are actually explained very simply I want you to test it out I want you folks to go check out our video content it was fun building all of this content and I want you to see how how some of these Concepts can be simplified and of course we'll always here to uh get your feedback improve some of the videos again nothing in this video content is static if you see a lot of people saying that okay I didn't understand this specific concept that we explained this way we go back and redo that video it's okay it's perfectly okay for us to do it because we want our students to be successful at the end of their course getting a flavor of what a real world AI problem solution is like that that's the key goal here we want undergraduate and graduate students who are just going into the job market understand what actually solving your AI or what solving a real world a problem looks like this will give you a flavor we have another course called applied a quartz.com which is much more broad which is which is typically targeted towards students who want to go and get an a job at the end of their undergraduate or graduate school this is more about doing a project getting a flavor of what what how things are in the real world and it will be fun I hope I hope you love some of this content and we're always here to hear your feedback and hope to see you in the applied a project course\n"