Python for Data Science (Free Online Course) : This course attempts to strike a balance between presenting the vast set of methods within the field of data science and Python programming techniques for implementing them. Problem-solving and programming implementation will be emphasized throughout the course. All techniques presented will be introduced using real-world programming examples. A major goal of the course is to ensure that when you finish the course, you will have the programming and conceptual expertise you need to join the field of data science.
Several Python modules, such as pandas, scikit-learn, scipy.stats, and statsmodels, will be introduced that are useful for data analysis, data visualization, and data mining. The course will gradually shift from introductory topics such as a review of Python, matrix operations, and statistics to applications and implementing programs involving data mining, visualization, statistical models, and time series analysis.
What You Will Learn?
| Unit 1: What is Data Science? |
| Unit 2: Python for Data Science |
| Unit 3: The numpy Module |
| Unit 4: Applied Statistics in Python |
| Unit 5: The pandas Module |
| Unit 6: Visualization |
| Unit 7: Data Mining I – Supervised Learning |
| Unit 8: Data Mining II – Clustering Techniques |
| Unit 9: Data Mining III – Statistical Modeling |
| Unit 10: Time Series Analysis |
Skills You Will Gain
- Python for Data Science
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Course Enrollment Process
Step 1 – Visit the Course Page
Click on the Orange Button below – GET THE FREE ONLINE COURSE to access the Course Page.
Step 2 – Sign Up or Log In
Click on the “Sign Up” or “Log In” button located at the top-right corner of the page. You can register using your email address, Google account, or Facebook account.
Step 3 – Enroll for FREE
Once you’re logged in, select the “Enroll Now” option to gain access to the course materials.
Step 4 – Begin Your Learning Journey: After clicking “Start Learning,” you will be seamlessly redirected to your personalized dashboard, where you can embark on your course at your own pace !
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