Data Science & Machine Learning Course by Sidrat Shafiq Khan

The Data Science & Machine Learning Course is a comprehensive, career-oriented program designed to help students build strong foundations in data analysis, programming, statistics, and artificial intelligence concepts. This course takes learners through a structured journey—from understanding basic data science principles to working with advanced tools, machine learning techniques, and real-world projects.

In today’s data-driven world, organizations across industries rely on data science professionals to extract insights, make informed decisions, and develop intelligent systems. This course is ideal for students, graduates, beginners, and aspiring professionals who want to enter the fields of data science, machine learning, and artificial intelligence.

By combining theoretical concepts with practical learning and hands-on projects, the program ensures that students not only understand core ideas but also gain the confidence to apply them in real-world scenarios.

What Students Will Learn

• Introduction to data science and its real-world applications
• Python programming for data science and analytics
• Working with libraries such as NumPy, Pandas, and Matplotlib
• Data collection methods and data cleaning techniques
• Understanding statistics and probability for data analysis
• Data visualization and storytelling with data
• SQL and database management fundamentals
• Machine learning concepts and algorithms
• Artificial intelligence basics and applications
• Deep learning frameworks such as TensorFlow, PyTorch, and Keras
• Introduction to tools, platforms, and industry workflows
• Version control and collaboration using GitHub
• Basics of HTML for data presentation
• Real-world projects and a capstone project for practical experience

Teaching Method

The course is available in both online and offline modes, offering flexibility to suit different learning preferences. Teaching methods include:

• Step-by-step conceptual explanations
• Hands-on coding practice sessions
• Live demonstrations of tools and techniques
• Interactive doubt-clearing sessions
• Real-world case studies and datasets
• Guided project development

Students will actively work on assignments and complete a capstone project to apply their knowledge and build a strong portfolio.

Why This Course

This program is designed to provide a balanced learning experience covering programming, mathematics, analytics, and machine learning. The structured curriculum ensures gradual skill development, starting from basic concepts and progressing toward advanced data science techniques. The focus on practical learning helps students build confidence and prepare for academic or professional opportunities in the data science domain.

Benefits and Outcomes

By completing this course, students will:

• Develop strong data science and analytical skills
• Gain practical experience using industry-relevant tools
• Understand machine learning and AI fundamentals
• Learn to clean, analyze, and visualize real-world data
• Build a portfolio through projects and capstone work
• Improve problem-solving and logical thinking abilities
• Explore career opportunities in data science and analytics

This course provides a complete learning pathway for anyone looking to start or advance their journey in data science and machine learning.