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About the Program

In these data science courses, you’ll learn how to use the Python language to clean, analyze and visualize data. Through our guided lectures and labs, you’ll get hands-on experience tackling interesting data problems. This is an action-packed learning path for data science enthusiasts who want to work with real world problems using Python. Make sure to take this learning path to solidify your data skills in Python, before diving into machine learning, big data and deep learning in Python.

Applied Data Science with Python: Course Outline

Course 1 – Python for Data Science

Effort: 5 hours Level: Beginner

This free Python course provides a beginner-friendly introduction to Python for Data Science. Practice through lab exercises, and you'll be ready to create your first Python scripts on your own!

Course 2- Data Analysis with Python

Effort: 8 hours Level: Beginner

In this course, you will learn how to analyze data in Python using multi-dimensional arrays in numpy, manipulate DataFrames in pandas, use SciPy library of mathematical routines, and perform machine learning using scikit-learn! You will learn how to perform data analytics in Python using these popular Python libraries and you will do it using hands-on labs using real Python tools like Jupyter notebook in JupyterLab.

Course 3 – Data Visualization with Python

Effort: 10 hours Level: Beginner

Data visualization is the graphical representation of data in order to interactively and efficiently convey insights to clients, customers, and stakeholders in general. It is a way to summarize your findings and display it in a form that facilitates interpretation and can help in identifying patterns or trends. In this Data Visualization with Python course, you'll learn how to create interesting graphics and charts and customize them to make them more effective and more pleasing to your audience.

Learning Path Courses

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    Python for Data Science

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    Data Analysis with Python

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    Data Visualization with Python

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