Python for Data Science Course Online (Self-Paced)

Unlock the power of Python for data-driven decision-making as you master Python programming fundamentals and dive into data analysis. Acquire essential skills to explore and manipulate data, create insightful visualizations, and perform statistical analysis, all through hands-on projects with real-world datasets.

Lesson 1: Python for Data Science Fundamentals
Lesson 2: Boolean Conditions
Lesson 3: Datetime & Random
Lesson 4: Loops & Strings
Lesson 5: Dictionaries
Lesson 6: Numpy
Lesson 7: Pandas Dataframes
Lesson 8: Bar Charts with Matplotlib
Lesson 9: Line & Scatter Charts with Matplotlib
Lesson 10: Pivot Population Data & Charts
  • 56 video lessons
  • 14 hours and 15 minutes of class content
  • Streaming access on desktop and mobile browsers
  • 100% satisfaction guarantee

Our bootcamp is meant to go from the very basics of Python programming to the start of machine learning with Python. In this Bootcamp, you’ll learn how and why Python is used for data science, how to create programs, work with data in Python, create data visualizations, and use statistics to create machine learning models.

Python Fundamentals

The course will start with the fundamentals of Python, including writing basic statements and expressions, creating variables, understanding different data types, working with lists, indexing and slicing lists, using functions and methods, and more. Concepts such as object-oriented programming are introduced.

Once a learning environment has been set up, we will work with different data types such as strings, lists, dictionaries, and tuples. Each data type has its own particular purpose and knowing when to use each one will be essential.

Structuring Programs

The second part of the course covers conditional statements and control flow tools. This includes the if/else statements, boolean operations, and different types of loops. These topics create a large portion of the logic in your code and this course will help you master these concepts. Learn to work with dictionaries, create functions, write for loops to iterate through data, and work with packages in Python.

Arrays & DataFrames

The third part of the course introduces operations and tools for data science. We will learn how to import and clean data using NumPy and Pandas. You’ll learn to work with Pandas DataFrames, wrangle data, and get descriptive statistics for your data.

Analyzing & Visualizing Data

You’ll learn to analyze and visualize data with key data science libraries including Pandas, NumPy, and Matplotlib. Learn to filter and clean data, group and pivot data, and start generating insights from your data with exploratory data analysis. Then create visualizations including bar charts, histograms, and advanced visualization for easy interpretation and sharing of your data insights.

Next Steps

After learning all the foundational Python programming and data analysis skills in this bootcamp, you will be ready to dive fully into machine learning.

This program builds off this foundational knowledge to turn you into a full machine learning data scientist. Pick up right where the Python for Data Science Bootcamp left off with advanced statistics and create machine learning models with logistic regressions, k-nearest neighbors, and decision trees.