This 45-part course consists of tutorials, quizzes, hands-on assignments and real-world projects to learn data science, as well as advanced python tools for data science.
- 10+ portfolio projects and 150+ exercises to give you a lot of practice and build fluency.
- Most of the tutorials are available in three different formats — video, long article and bite-sized cards — so you can learn the way that works best for you.
- Articles and videos have code execution built-in. You can play the instructor's code right inside the video!
- Exceptional content quality. We teach you the real thing, no dumbing things down or only talking about the easiest use case.
- We collect ratings on every tutorial and project. Anything with average rating below 4.5 is sent back for revision.
Trillions of gigabytes of data are being produced yearly, and the number is still growing exponentially. However, data is only a raw material, and Data Science is the field which enables us to extract information from it.
Data Scientists are in demand in virtually every company to drive strategic decisions and power their business. It was ranked the #1 Job by Glassdoor with an average salary of over $120,000.
- Become familiar with all the key components of data science — programming, statistics and probability, data analysis and exploration, and machine learning.
- Learn advanced Python data science libraries such as NumPy, Pandas, Matplotlib, Seaborn and Scikit-learn.
- Understand machine learning concepts and algorithms. Apply them to problems in image classification, sentiment classification, movie recommendations, etc.
- Become comfortable with the the end-to-end workflow of a typical data science project - starting from data cleaning and analysis and going all the way to interpreting results and machine learning models.
- Attain fluency and build a portfolio by implementing many real-world projects using above techniques.
Related course: Machine Learning.
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