Ultimate-Job-Ready-Data-Science
This all-in-one Job-Ready Data Science Course designed for beginners and intermediate learners to master data science skills and become industry-ready with hands-on experience.
Meet Your Instructor: CodeWithHarry
Haris Ali Khan, widely recognized as CodeWithHarry, stands as one of India's most beloved and influential programming educators, having simplified coding for millions of learners worldwide. As a software engineer, educator, and content creator with an extensive YouTube following, Harry has revolutionized the way programming is taught in India by creating practical, beginner-friendly tutorials that focus on building real-world coding skills. His teaching philosophy centers on making complex programming concepts accessible to everyone, regardless of their technical background. From Python fundamentals to advanced web development, data science, and machine learning, CodeWithHarry's comprehensive course library covers the entire spectrum of programming education, empowering countless students to kickstart their careers in technology.
Experience: 8+ years
Students Helped: 4,000,000+
Specialization: Full-Stack Development & Data Science Education
Course Overview
This comprehensive course is designed to take you from foundational concepts to advanced implementation in full-stack development & data science education. You'll learn through project-based learning with beginner-friendly explanations, emphasis on hands-on coding practice, and focus on real-world applications, building real-world projects that demonstrate your skills and enhance your portfolio.
Whether you're looking to start a new career in technology or advance your current skills, this course provides the structured learning path and practical experience you need to succeed in today's competitive tech industry.
Course Curriculum
Course Syllabus
Introduction to Data Science
Understanding the Conda Environment
Python Refresher (For Data Science)
Project 1 Coders of Delhi
Data analysis using NumPy
Data Analysis using Pandas
Data Visualization using Matplotlib and Seaborn
Data Collection Techniques
SQL for Data Science
Probability
Probability Distributions and Central Limit Theorem
Machine Learning for Data Scientists
Types of ML Algorithms
Practical ML using Scikit-learn
Deep Learning & Neural Networks
Web Development for Data Scientists
Large Language Models
Leveraging AI as a Data Scientist
Git for Data Scientists
Project 2 RAG based AI Teaching Assistant
Conclusion
Bonus Videos
Requirements
- No prior experience in data science is needed
- Basic computer skills and internet access
- Willingness to learn and solve real-world problems
- Curiosity and consistency
- Stable internet connection for accessing course content
- Basic familiarity with using the terminal/command line (helpful but not required)
Course Features
Course Details
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