Python for Data Science Course Online

Self-paced online training with expert support

Harness the power of Python for data-driven decision-making by mastering the fundamentals of Python programming and data analysis. Develop key skills to explore, manipulate, and analyze data, create meaningful visualizations, and perform statistical analysis, all through hands-on projects using real-world datasets.

$1,495 Start anytime

This course includes

  • 30 hours of project-based training from experts
  • Answers from real instructors
  • Verified digital certificate of completion
  • Learn at an accredited institution

This course is self-paced. for live online or in-person instruction, take the Python for Data Science Bootcamp.

This course is designed to equip you with the essential tools and skills for analyzing and visualizing data, making confident predictions, and solving real-world challenges in data science. Get a strong foundation in Python programming, exploring libraries such as Pandas, NumPy, and Matplotlib to handle data efficiently and create compelling visualizations. You’ll also gain valuable insights into machine learning concepts and how to implement them through Python. Structured to suit learners of all levels, the course ensures hands-on experience by emphasizing practical, project-based learning. Expert instructors are committed to guiding and supporting you at each stage of your educational path, enabling success in this dynamic field.

Beginning with Python fundamentals, we cover key concepts such as writing basic statements, creating variables, understanding data types, and working with lists. You’ll also learn how to index, slice lists, and use functions and methods. Object-oriented programming concepts will also be introduced to enhance your coding skills. Next, we dive into conditional statements and control flow tools like If/Else Statements, Boolean operations, and loops. These concepts form the core logic of your code, and you’ll gain hands-on experience creating dictionaries, writing functions, and iterating through data using for loops and working with Python packages.

In the third part of the course, you'll explore data science operations with NumPy and Pandas. You’ll learn to import, clean, and manipulate data, work with Pandas dataframes, and calculate descriptive statistics for your datasets. Learn how to analyze and visualize data using essential data science libraries such as Pandas, NumPy, and Matplotlib. You'll practice filtering and cleaning data, grouping and pivoting it, and performing exploratory data analysis. You will then create a variety of visualizations, such as bar charts and histograms, to effectively communicate your insights.

This course has a prerequisite

This course is open to beginners. Students must be comfortable using a computer. No other prior knowledge is required.

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