What You Will Learn

This course covers essential topics in Data Science and Machine Learning using Python. You will start from the basics and progress to advanced concepts through practical projects.

Core Topics Included

• Python Programming Fundamentals: Learn about variables, data types, operators, conditional statements, loops, functions, and object-oriented programming.

• Data Analysis with Python: Understand how to use NumPy and Pandas for data manipulation. Learn data cleaning, transformation, and aggregation.

• SQL for Data Analytics: Gain knowledge in database fundamentals, SQL queries, joins, and aggregate functions.

• Statistics for Data Science: Explore descriptive statistics, probability concepts, hypothesis testing, and correlation analysis.

• Data Visualization: Use Matplotlib, Seaborn, and Plotly to create visual representations of data and dashboards.

• Machine Learning Fundamentals: Learn about data preprocessing, feature engineering, model evaluation metrics, and algorithms like linear regression and decision trees.

• Advanced Machine Learning: Study ensemble learning, hyperparameter tuning, clustering, and dimensionality reduction.

• Deep Learning & Artificial Intelligence: Understand neural networks, TensorFlow, Keras, and applications of AI.

• Real-World Industry Projects: Work on projects like customer churn prediction, house price prediction, and recommendation systems.

• Career & Interview Preparation: Learn about resume building, LinkedIn optimization, and mock interviews.

Learning Progression

You will start with Python programming, then move to data analysis and SQL. After gaining statistical knowledge, you will learn data visualization techniques. The course will then cover machine learning and advanced concepts, concluding with deep learning and real-world projects.

This structured approach ensures that you build your skills step by step, from beginner to advanced levels.