Data Science & Machine Learning (Theory + Projects) – A-Z (90 Hours)

A Deep, Structured Program to Learn Data Science, Machine Learning & Deep Learning with Python

Course Overview

Data Science & Machine Learning (Theory + Projects) – A-Z (90 Hours) is a long-form, in-depth learning program designed for learners who want both strong theoretical understanding and hands-on implementation.

This course takes a ground-up approach, starting with core Python and data concepts, then gradually moving into statistics, machine learning, and deep learning, all supported by live coding and practical projects.

Instead of rushing through tools, the program focuses on why algorithms work, how data behaves, and how models are built and improved in real-world scenarios.

Key Course Details

• Instructor: AI Sciences
• Level: Beginner to Advanced
• Language: English
• Total Duration: ~94 Hours
• Students Enrolled: 7,500+
• Rating: ⭐ 4.3 / 5
• Certificate: ✅ Yes
• Access: Lifetime (Mobile & TV)

Data Science Career Path: 100 Days of Data Science Bootcamp

Start Course

What You Will Learn

Python for Data Science

• Python fundamentals for data analysis
• Working with NumPy, pandas, and Matplotlib
• Data handling, indexing, and transformations

Data Understanding & Visualization

• Exploring real datasets effectively
• Visualizing trends and patterns using Python
• Creating meaningful charts and plots

Probability & Statistics

• Core probability concepts explained intuitively
• Statistical thinking for data science
• Applying statistics using Python code

Machine Learning Foundations

• Understanding how machine learning works
• Supervised and unsupervised learning concepts
• Building ML models using Python and scikit-learn

Feature Engineering & Optimization

• Preparing data for better model performance
• Feature selection and transformation
• Dimensionality reduction techniques

 Deep Learning with Python

• Artificial Neural Networks (ANNs) fundamentals
• Convolutional Neural Networks (CNNs) concepts
• Understanding how deep learning models learn patterns

Practical Coding & Projects

• Live coding walkthroughs
• Applying concepts to realistic datasets
• Learning how to build simple AI-powered applications

Learning Style & Structure

• Step-by-step progression from basics to advanced topics
• Theory explained first, followed by practical implementation
• Long-form lessons for deeper understanding
• Designed to build confidence gradually

Who This Course Is For

• Beginners entering Data Science or Machine Learning
• Learners from non-engineering backgrounds
• Business analysts wanting technical data skills
• Students seeking a single, comprehensive DS + ML program
• Anyone interested in AI, data, and predictive modeling

 Why This Course Stands Out

• Focuses equally on theory and implementation
• Covers Data Science + Machine Learning + Deep Learning in one program
• Long-duration format allows deeper topic coverage
• Suitable for learners who prefer structured, detailed explanations

One Honest Limitation

This is a long and detailed course.
It’s best suited for learners who are patient and willing to invest time rather than those looking for quick crash courses.

Final Takeaway

If you are looking for a comprehensive A-Z journey covering data science, machine learning, and deep learning with Python — all in one place — this course offers a solid, theory-backed, practice-oriented path.

It’s especially valuable for learners who want to understand concepts deeply, not just apply libraries blindly.