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### Statistical embedding: Beyond principal components

There has been an intense recent activity in embedding of very high dimensional and nonlinear data structures, much of it in the data science and machine learning literature. We survey this activity in four parts. In the first part we cover nonlinear methods such as principal curves, multidimensional scaling, local linear methods, ISOMAP, graph based methods and kernel based methods. The second part is concerned with topological embedding methods, in particular mapping topological properties into persistence diagrams. Another type of data sets with a tremendous growth is very high-dimensional network data. The task considered in part three is how to embed such data in a vector space of moderate dimension to make the data amenable to traditional techniques such as cluster and classification techniques. The final part of the survey deals with embedding in \$\mathbb{R}^2\$, which is visualization. Three methods are presented: \$t\$-SNE, UMAP and LargeVis based on methods in parts one, two and three, respectively. The methods are illustrated and compared on two simulated data sets; one consisting of a triple of noisy Ranunculoid curves, and one consisting of networks of increasing complexity and with two types of nodes.

### Math for Data Science and Machine Learning: University Level

In this course, we will learn math for data science and machine learning. We will also discuss the importance of Math for data science and machine learning in practical words. Moreover, Math for data science and machine learning course is a bundle of two courses of linear algebra and probability and statistics. So, students will learn the complete contents of probability and statistics, and linear algebra. It is not like that you will not complete all the contents in this 7 hours video course.

### Data Science Curriculum for Professionals - KDnuggets

If you have finally decided to take the path from Excel-copy-and-paste to reproducible data science, then you will need to know the best route to take. The good news is that there is an abundance of free resources to get you there and awesome online communities to help you along the way. The bad news is that it can get overwhelming to pick which resources to take advantage of. This here is a no-nonsense guide that you can follow without regret, so you can spend less time worrying about the trail and more time trekking it. It's based on the lessons I learned when I went from a renewable energy project engineer who had never taken a statistics class to the head of a major data platform. At the trailhead for this journey, you can find an army of educated individuals doing data analysis by necessity, not passion.

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### We're Building a Data Science Curriculum with Advanced Mathematics and Machine Learning

We're expanding freeCodeCamp's Python section into a full-blown data science curriculum and we need your help. Currently, these data science skills are only taught at a few universities around the world. Our goal is for anyone, anywhere to be able to learn these advanced mathematics and machine learning concepts and that data scientists use in the field. You'll be able to code your way through a series of hundreds of Python projects to earn certifications in: You'll be able to build these projects in your browser or offline in your operating system. You'll use Jupyter Notebooks filled with interactive graphs, datasets, and automated tests to check your code.

### Top Data Science Education Initiatives By Institutions In 2020

While normal education suffered a standstill in 2020, there were a lot of online courses and programs that were initiated by some of the most prestigious institutions as well as big tech giants so that the process of learning and skill development doesn't suffer. As the trend has been for a few years now, some of the most interesting initiatives were seen in the field of data science. In this article, we have listed some of the prominent data science education programs and initiatives in 2020. Microsoft, in collaboration with Netflix, has launched three new learning modules on beginners concepts in data science, along with machine learning and artificial intelligence. The design of these courses is inspired by the Netflix original film -- 'Over The Moon,' where a young girl Fei Fei, who builds a rocket to the moon, embarks on a mission to prove the existence of Moon Goddess.

### Comprehensive Project Based Data Science Curriculum

This is where you'll improve your coding abilities, math understanding and start working on real data science problems. In this respect, I highly recommend taking what I consider is the best data science boot camp out there: Le Wagon. With a heavy emphasis on practical exercises and a final project in which you get to deploy your own machine learning model, this highly intensive boot camp will give you a big picture data science end to end: just enough theory, data wrangling, data viz, programming inside an IDE, Git, machine learning, deep learning, data engineering. Once you understand and have worked on the most important parts of data science, you'll have a better idea of what you like, what your strengths and weaknesses are, and where to head next. This is also an opportunity to build your network.

### Microsoft Partners With Netflix To Create New Data Science Learning Modules

With the increasing requirement for more data scientists, ML experts, and AI engineers in every industry, Microsoft, in partnership with Netflix, has launched three new learning modules to guide learners through beginning concepts in data science, machine learning and artificial intelligence. Inspired by the new Netflix original film -- 'Over the Moon' these learning modules include three paths -- planning a Moon mission using the Python Pandas Library; predicting meteor showers using Python and VC Code; and using AI to recognise objects in images using Azure Custom Vision. The growing requirement of data scientists comes with criteria of having a broad set of skills from data analysis with no-code and low-code solutions which will help them with designing and writing intricate ML models and solve some of the planet's most difficult problems. Keeping this in mind, Microsoft, partnering with Netflix, has launched these modules for providing high quality, free content to help learners develop their skills depending based on their professional goals and personal interests. According to Microsoft's blog post, "One such endeavour in creating an opportunity for you to learn and upskill is through unique partnerships. In the summer of 2020, we launched a set of Microsoft Learn modules inspired by real NASA scientists and engineers at https://aka.ms/LearnInSpace. And this Fall we are excited to bring you three more Microsoft Learn modules inspired by the new Netflix Original Over the Moon."

### Turning Software Engineers into AI Engineers

In industry as well as education as well as academics we see a growing need for knowledge on how to apply machine learning in software applications. With the educational programme ICT & AI at Fontys UAS we had to find an answer to the question: "How should we educate software engineers to become AI engineers?" This paper describes our educational programme, the open source tools we use, and the literature it is based on. After three years of experience, we present our lessons learned for both educational institutions and software engineers in practice.