Description

This 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, and 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, and using functions and methods. 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 form a large portion of the logic in your code, and this course will help you master them. Learn to work with dictionaries, create functions, write 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 visualizations, 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.

Course Overview

Python Fundamentals: Variables & Data Types

Declare variables of basic types: integers, floats, strings, booleans
Perform input/output with print() and input()
Apply arithmetic, relational, and logical operators

Control Flow I: Conditional Logic

Use Boolean operators ==, !=, <, >, <=, >=
Write if/else and nested conditionals
Combine conditions with and/or for complex logic

Control Flow II: Loops & Iteration

Implement for loops over ranges and lists; understand iterables
Understand map and filter operations.
Use list comprehensions to simplify operations.

DataFrames & Data Manipulation with Pandas

Construct DataFrames from various data formats via pd.DataFrame()
Concatenate multiple DataFrames using pd.concat()
Inspect DataFrame shape and handle missing values (NaN)
Perform Panda data analysis operations to glean insight

Data Visualization: Charting Basics

Plot time series with plt.plot() for line charts
Create scatter plots using plt.scatter() to reveal correlations
Decide between line vs. scatter based on data context and purpose

Trend Analysis with Regression Lines

Understand least-squares regression concept and its interpretation
Compute a best-fit line via numpy.polyfit()
Overlay regression lines on scatter plots and make predictions

Advanced Plot Customization

Annotate charts with titles, axis labels, and legends
Highlight key data points (e.g., min/max) directly on plots
Use stacked bar charts, pie charts, and animated charts to visualize data

Python for Data Science Bootcamp Virtual Classroom Live September 08, 2025

Price: $1,495

Enroll today to reserve your spot!

Description

Python Fundamentals

Structuring Programs

Arrays & Dataframes

Analyzing & Visualizing Data

Next Steps

Course Overview

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