Python for Data Science: The Complete Data Science Bootcamp

Name: Python for Data Science: The Complete Data Science Bootcamp
Rating: 4.2 (16 reviews)

Python for Data Science: Perform Data Analysis, Visualization, and Machine Learning With Python

Created byMuhammad Riaz Uddin

Last updated 1/2026

English

What you'll learn

What is Data Science?
Why Python for Data Science?
Introduction to Jupyter Notebooks
Variables, Data Types, and Operators
Control Flow: Conditionals and Loops
Working with Modules and Packages
Error Handling and Assertions
Introduction to Pandas: Series and DataFrames
Reading & Writing Data (CSV, Excel, JSON)
Data Cleaning & Preprocessing
Handling Missing Values & Duplicates
Data Transformation & Feature Engineering
Creating, Indexing, and Slicing Arrays
Mathematical Operations with NumPy
Useful NumPy Functions for Data Science
Introduction to Data Visualization
Plotting with Matplotlib
Seaborn for Statistical Graphics
Advanced Charts: Heatmaps, Pairplots, and Violin Plots
Identifying Patterns, Outliers & Trends
Using Pandas Profiling & Sweetviz

Course content

9 sections • 44 lectures • 3h 54m total length

What is Data Science?4:43
Why Python for Data Science?4:52
Introduction to Jupyter Notebooks1:14
Explore Jupyter notebooks, an open source web application that lets you write and run code in one interface, add text, images, and latex for data analysis, visualization, and documentation.
First Python Script: “Hello, Data!”5:37

Introduction to Pandas: Series and DataFrames6:15
Learn to read and write data with pandas, loading csv, excel, and json files, and save outputs with to_csv, to_excel, and to_json, controlling delimiter, index, and sheet.
Reading & Writing Data (CSV, Excel, JSON)6:14
Data Cleaning & Preprocessing7:43
Handling Missing Values & Duplicates7:58
Data Transformation & Feature Engineering7:33
Explore data transformation and feature engineering with pandas by creating new features such as salary over 60000, age groups, name length, and one-hot encoding to improve machine learning input.
Grouping, Sorting, and Aggregating Data6:07

What is Machine Learning?3:11
Explore machine learning by training models on data to learn patterns and predict outcomes, illustrated with a linear regression demo and the three learning types: supervised, unsupervised, and reinforced learning.
Supervised vs. Unsupervised Learning5:27
ML Workflow (Prepare, Train, Evaluate, Tune)5:00
Regression Algorithms: Linear, Ridge, Lasso6:37
Classification Algorithms: Logistic Regression, KNN, Decision Trees6:26
Clustering: K-Means2:54

Introduction to Time Series Analysis5:38
Develop hands-on time series analysis by creating a monthly data series with pandas, numpy, and matplotlib, and decompose it into trend, seasonality, and residual using an additive model.
Intro to Deep Learning with TensorFlow/Keras5:58
Explore deep learning with tensorflow and keras by building a mnist classifier. Train the model and evaluate accuracy, with future topics like cnn and model tuning.
Working with Big Data (Intro to PySpark)5:53

Requirements

No prior data science experience needed

Description

Python for Data Science is the most in-demand skill for data analysts, data scientists, and machine learning engineers. This course is a complete, beginner friendly, and practical guide to learning data science using Python — no prior experience required.

You’ll learn how to analyze data, clean datasets, visualize insights, and work with real-world data using the most popular Python libraries used by professionals in the industry.

This course focuses on hands-on learning, helping you build real data science skills you can apply immediately in projects, jobs, and interviews.

What You’ll Learn

By the end of this course, you will be able to:
Use Python for data science and data analysis
Work confidently with NumPy and Pandas
Clean, transform, and manipulate real world datasets
Perform Exploratory Data Analysis (EDA)
Visualize data using Matplotlib and Seaborn
Understand basic statistics for data science
Apply Python to solve real business and data problems
Build a strong foundation for machine learning and AI

Why This Course Works

Beginner friendly with step by step explanations
Hands-on coding exercises and practice datasets
Real world examples used by data professionals
Clear explanations without unnecessary complexity
Designed for career growth and job readiness

Why Learn Python for Data Science?

Python is the #1 programming language for data science, analytics, and machine learning. By mastering Python for data science, you open the door to high paying roles, data driven decision making, and advanced technologies like AI and machine learning.

Enroll now and start your journey into Python for Data Science with confidence.

Who this course is for:

Anyone who wants to work with data using Python
Students preparing for data science or analytics careers
Beginners who want to learn Python for Data Science
Professionals looking to switch into data analytics or data science

Python for Data Science: The Complete Data Science Bootcamp

What you'll learn

Explore related topics

Course content

Introduction to Data Science and Python4 lectures • 16min

Python Fundamentals for Data Science5 lectures • 33min

Working with Data Using Pandas6 lectures • 42min

Numerical Computing with NumPy5 lectures • 23min

Data Visualization5 lectures • 29min

Exploratory Data Analysis (EDA)5 lectures • 23min

Introduction to Statistics for Data Science5 lectures • 22min

Machine Learning with Scikit-Learn6 lectures • 30min

Advanced Topics (Optional / Bonus)3 lectures • 17min

Requirements

Description

Who this course is for: