What courses to choose if you want to boost your Data Science career<\/h2>\n<\/p>\n\n\n\n<\/p>\n![\"Przemek](\"https:\/\/miro.medium.com\/fit\/c\/96\/96\/1*Un4ofSyOspYd5_1AUJiFSg.jpeg\")
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Learning online became one of the most popular forms of learning. With great platforms like MIT OCWare, Udemy and Coursera, anyone at any level can find something to learn from. In this post I want to highlight top Data Science Courses available right now on Coursera.<\/p>\nNever stop learning!<\/figcaption><\/figure>\nYou are just starting, you want to learn the basics of Python and how to compile your first data science models. You haven\u2019t done much data science or statistics before, you\u2019ve heard a couple of terms, but those are just buzzwords for you right now. You want to build your knowledge from the ground up.<\/p>\n
Introduction to Data Science in Python<\/a> from University of Michigan is one of the two most popular introductory courses right now. It doesn\u2019t assume anything, you\u2019ll start with Python, and then go through different data structures (pandas!) and how to manipulate them. Perfect for beginners. Another popular course from UMich is Python Data Structures<\/a>, which is also recommended for beginners.<\/p>\nIBM Data Science<\/a> is a professional certificate which is composed of 9 courses. It starts slowly by explaining what is Data Science, what methodology and tools one uses, to go into data processing and data visualization, to finally arrive at machine learning. This is a great certificate to have on your resume, whether you\u2019re just starting or you\u2019ve done a bit of data science already.<\/p>\nLast but not least, if you want to get into data science, you need learn some mathematics and statistics. Don\u2019t worry, not that much, but still you should be comfortable with doing operations on vectors, matrices, know what is a mean, variance, bias and be able to compute some probabilities. This course explains just that: Data Science Math Skills<\/a> from Duke University.<\/p>\nYou have some experience, you\u2019ve started to feel confident in Python, you\u2019ve done some experiments and now you look to expand your knowledge. Machine Learning is probably what you should pick up at this point.<\/p>\n
Machine Learning Specialization<\/a> by University of Washington is a perfect way to start your adventure with machine learning. This course assumes you\u2019re fine with Python, know data structures and takes you through fundamental concepts of machine learning: classification and clustering algorithms. 4 courses in 1 specialization.<\/p>\nApplied AI course by IBM<\/a> is a great dive into deep learning and deploying deep learning models on a cloud. You will learn about deep learning frameworks like Keras and Tensorflow (if you don\u2019t know about them already). It\u2019s really about deployment.<\/p>\nYou have at least a couple of years of experience, you\u2019re an expert in Python and using data science to extract information. You\u2019re looking to consolidate your knowledge, put it all together and see what\u2019s the most recent developments in Data Science.<\/p>\n
Machine Learning course<\/a> by Andrew Ng offered at Stanford is now a classic. Coursera was co-founded by Andrew Ng and this was one of the very first course on the platform. There are more up-to-date courses, but this one still manages to show you a theory behind machine learning very well. Highly recommended!<\/p>\n
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Learning online became one of the most popular forms of learning. With great platforms like MIT OCWare, Udemy and Coursera, anyone at any level can find something to learn from. In this post I want to highlight top Data Science Courses available right now on Coursera.<\/p>\n You are just starting, you want to learn the basics of Python and how to compile your first data science models. You haven\u2019t done much data science or statistics before, you\u2019ve heard a couple of terms, but those are just buzzwords for you right now. You want to build your knowledge from the ground up.<\/p>\n Introduction to Data Science in Python<\/a> from University of Michigan is one of the two most popular introductory courses right now. It doesn\u2019t assume anything, you\u2019ll start with Python, and then go through different data structures (pandas!) and how to manipulate them. Perfect for beginners. Another popular course from UMich is Python Data Structures<\/a>, which is also recommended for beginners.<\/p>\n IBM Data Science<\/a> is a professional certificate which is composed of 9 courses. It starts slowly by explaining what is Data Science, what methodology and tools one uses, to go into data processing and data visualization, to finally arrive at machine learning. This is a great certificate to have on your resume, whether you\u2019re just starting or you\u2019ve done a bit of data science already.<\/p>\n Last but not least, if you want to get into data science, you need learn some mathematics and statistics. Don\u2019t worry, not that much, but still you should be comfortable with doing operations on vectors, matrices, know what is a mean, variance, bias and be able to compute some probabilities. This course explains just that: Data Science Math Skills<\/a> from Duke University.<\/p>\n You have some experience, you\u2019ve started to feel confident in Python, you\u2019ve done some experiments and now you look to expand your knowledge. Machine Learning is probably what you should pick up at this point.<\/p>\n Machine Learning Specialization<\/a> by University of Washington is a perfect way to start your adventure with machine learning. This course assumes you\u2019re fine with Python, know data structures and takes you through fundamental concepts of machine learning: classification and clustering algorithms. 4 courses in 1 specialization.<\/p>\n Applied AI course by IBM<\/a> is a great dive into deep learning and deploying deep learning models on a cloud. You will learn about deep learning frameworks like Keras and Tensorflow (if you don\u2019t know about them already). It\u2019s really about deployment.<\/p>\n You have at least a couple of years of experience, you\u2019re an expert in Python and using data science to extract information. You\u2019re looking to consolidate your knowledge, put it all together and see what\u2019s the most recent developments in Data Science.<\/p>\n Machine Learning course<\/a> by Andrew Ng offered at Stanford is now a classic. Coursera was co-founded by Andrew Ng and this was one of the very first course on the platform. There are more up-to-date courses, but this one still manages to show you a theory behind machine learning very well. Highly recommended!<\/p>\n