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 designed to take you from the fundamentals of Python programming to the early stages of machine learning with Python. In this bootcamp, you will learn how and why Python is used in data science, how to build programs, work with data, create visualizations, and apply statistics to machine learning models.
Python Fundamentals
The course begins with the core concepts of Python, including writing basic statements and expressions, creating variables, understanding data types, working with lists, indexing and slicing, and using functions and methods. You will also receive an introduction to object-oriented programming.
After setting up your learning environment, you will work with a variety of data types such as strings, lists, dictionaries, and tuples. Each data type serves a different purpose, and understanding when to use each one is an essential programming skill.
Structuring Programs
The second part of the course focuses on conditional statements and control flow. Topics include if and else statements, Boolean logic, and different types of loops. These concepts form much of the decision-making structure in code and are key to writing effective programs. You will also learn to work with dictionaries, create functions, use loops to iterate through data, and manage packages in Python.
Arrays and DataFrames
The third part of the course introduces important tools for data science. You will learn how to import and clean data using NumPy and Pandas, work with Pandas DataFrames, wrangle data, and generate descriptive statistics.
Analyzing and Visualizing Data
You will learn to analyze and visualize data using essential data science libraries, including Pandas, NumPy, and Matplotlib. Topics include filtering and cleaning data, grouping and pivoting data, and using exploratory data analysis to uncover insights. You will also create visualizations such as bar charts, histograms, and other advanced charts that make findings easier to interpret and share.
Next Steps
After building foundational Python programming and data analysis skills in this bootcamp, you will be ready to move further into machine learning.
This program serves as the foundation for more advanced study in machine learning and data science. From here, you can continue by learning advanced statistics and building machine learning models using methods such as logistic regression, k-nearest neighbors, and decision trees.
