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Learn Data Science

This course will help you start your journey to becoming a data scientist. You’ll learn the basic ideas, useful tools, and real-life examples you need to begin your career.

4.8
30 Lessons
2 Mock Interviews
4h
Updated 1 week ago
Join 3 million developers at
Join 3 million developers at
LEARNING OBJECTIVES
  • Explore the fundamentals of data science, including its purpose, key components, and real-world applications.
  • Analyze data science problems using the data science pipeline, from identifying questions to deploying predictive models.
  • Access and manipulate data from various sources using Python, including CSV, JSON, and APIs.
  • Utilize SQL to retrieve, filter, and organize data from relational databases for effective analysis.
  • Clean and prepare datasets by identifying and fixing common data issues such as missing values and duplicates.
  • Build and evaluate machine learning models using regression and classification techniques to generate predictions.
KEY OUTCOMES
Ace Data Science Interviews

Demonstrate your ability to solve data science problems and articulate your approach in interviews, showcasing practical skills and knowledge.

Implement SQL Queries for Analysis

Retrieve and analyze data from relational databases using SQL, enabling you to extract actionable insights for decision-making.

Build Predictive Models

Create and evaluate machine learning models using Python, translating data into actionable insights for real-world applications.

Prepare Data for Analysis

Clean and preprocess datasets effectively, ensuring data quality and reliability for accurate analysis and modeling.

Learning Roadmap

30 Lessons33 Quizzes

1.

Dive into Data Science

Dive into Data Science

Explore what data science is and why it matters.

3.

Clean It Up

Clean It Up

6 Lessons

6 Lessons

Fix, shape, and prepare data for analysis.

4.

Make Sense of Data

Make Sense of Data

5 Lessons

5 Lessons

Understand and visualize data patterns and stats.

5.

Build Smart Stuff

Build Smart Stuff

7 Lessons

7 Lessons

Apply models to predict, classify, and cluster.

7.

Appendix

Appendix

3 Lessons

3 Lessons

Explore career guidance, resources, and steps to become a data scientist.
Certificate of Completion
Showcase your accomplishment by sharing your certificate of completion.
Fahim Ul HaqLearn Data ScienceFounder & CEO
Developed by MAANG Engineers
ABOUT THIS COURSE
As data becomes central to decision-making across industries, the ability to learn data science is quickly becoming a foundational skill. From product decisions to healthcare insights, data science drives how organizations understand and act on information. This course is designed to help you move beyond surface-level exposure and build a practical, structured understanding of data science. I built this course from my experience teaching data-driven thinking and working with intelligent systems, where I consistently saw beginners struggle to connect tools with real problem-solving. The challenge was the lack of a clear starting point. This course addresses that by guiding you step by step, focusing on how to think through data science problems, not just execute them. You’ll start with core concepts and real-world use cases, then work with data using SQL and Python (pandas). You’ll clean, explore, and visualize datasets before building simple machine learning models to generate predictions and insights. If you want to learn data science in a practical, beginner-friendly way, this course provides a clear path to get started.
ABOUT THE AUTHOR

Khayyam Hashmi

Computer scientist and Generative AI and Machine Learning specialist. VP of Technical Content @ educative.io.

Learn more about Khayyam

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