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Bestseller

Data Science & Algorithms in Python

Learn Data Science from scratch and master machine learning, data analysis, and visualization.

J
John Smilga
Data Scientist & Python Expert
4.6 (12.5K Reviews)
60% Completed
Level
Beginner to Advanced
Lessons
42 Lessons
Duration
12h 45m
Students
25,000+
Certificate
Yes

Course Introduction

This comprehensive data science course covers everything from Python basics to advanced machine learning algorithms. You'll learn to analyze data, build predictive models, and create stunning visualizations. By the end, you will be confident working with real-world datasets and deploying ML solutions. This course has helped thousands of students land jobs at top companies including Google, Amazon, and Microsoft.

What you'll learn

Python for Data Science
Data Analysis & Visualization
Machine Learning Algorithms
Deep Learning Basics
Data Cleaning & Preprocessing
Statistical Analysis
Real-world Projects
Deploy ML Models

Course Preview

DATA
Full Course
For Beginners
05:20 / 12:45

Watch this preview video to get a feel for the course content and teaching style.

1. Introduction to Data Science

5 min read

Data Science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from structured and unstructured data.

  • What is Data Science?
  • Key Skills Required
  • Applications of Data Science

2. Python for Data Science

8 min read

Python has become the de-facto language for data science due to its simplicity and the rich ecosystem of libraries. NumPy, Pandas, Matplotlib, Seaborn, Scikit-Learn, TensorFlow and PyTorch are the core tools every data scientist must master.

  • Installing Python & Anaconda
  • NumPy Arrays and Operations
  • Pandas DataFrames and Series
  • Reading CSV, Excel, JSON files

3. Data Analysis Fundamentals

6 min read

Exploratory Data Analysis (EDA) is the critical process of performing initial investigations on data to discover patterns, spot anomalies, test hypotheses and check assumptions with the help of summary statistics and graphical representations.

Data Science Cheat Sheet
PDF • 2.4 MB
Download
Python Libraries Guide
PDF • 1.8 MB
Download
Datasets Bundle
ZIP • 45 MB
Download
ML Algorithms Notebook
IPYNB • 3.2 MB
Download

Video library available after enrollment.

Enroll Now
7 sections • 42 lectures • 12h 45m total length
1. Introduction to Data Science 5/5
What is Data Science?
5:20
Applications & Examples
7:15
Tools Overview
6:30
Python Setup
8:45
Chapter Quiz
10 Questions
2. Python for Data Science 0/6
3. Data Analysis 0/7
4. Data Visualization 0/6
5. Machine Learning 0/8
6. Deep Learning Basics 0/5
7. Projects 0/5
J

John Smilga

Data Scientist & Python Expert

4.6 Rating 45,000+ Students 12 Courses

An industry expert with 10+ years of real-world experience in data science, machine learning, and software development. Passionate about making complex topics accessible to everyone through clear, practical, project-based teaching. Known for clean explanations and hands-on approaches that actually get students hired.

Python Machine Learning Data Analysis Deep Learning SQL Statistics
4.6
Course Rating
72%
18%
6%
3%
1%
A
Arjun Sharma
2 weeks ago

Absolutely fantastic course! John explains complex concepts in such a simple way. The projects are real-world and helped me land my first data science job!

P
Priya Menon
1 month ago

Best data science course on the platform. The curriculum is well-structured and the hands-on projects make the learning stick. Highly recommend!

R
Rahul Gupta
3 weeks ago

Very comprehensive content. I appreciate how each concept builds on the previous one. Would love more advanced deep learning content but overall excellent.

V
Vikram K 3 days ago
Which version of Python should I use for this course?
John Smilga: Python 3.9 or above is recommended. The Anaconda distribution is easiest to set up as it comes with most libraries pre-installed.
S
Sunita R 1 week ago
Can I access the course materials offline?

Course Progress

60% Completed
25/42
Lessons
10h 15m
Time Spent
3
Certificates

Course Content

1. Introduction to Data Science 5/5
What is Data Science? 5:20
Applications & Examples 7:15
Tools Overview 6:30
Python Setup 8:45
Chapter Quiz 10 Questions
2. Python for Data Science 0/6
3. Data Analysis 0/7
4. Data Visualization 0/6
5. Machine Learning 0/8
6. Deep Learning Basics 0/5
7. Projects 0/5

Course Resources

Data Science Cheat Sheet
PDF • 2.4 MB
Download
Python Libraries Guide
PDF • 1.8 MB
Download
Datasets Bundle
ZIP • 45 MB
Download
ML Algorithms Notebook
IPYNB • 3.2 MB
Download
View all resources