Data Science with Machine Learning is an immersive program designed to equip learners with the skills required to analyze data, build machine learning models, and deploy AI-driven solutions. This course begins with foundational concepts, such as Python programming and data manipulation, and progresses to advanced machine learning algorithms.

Throughout the course, students will work on real-world datasets, applying data preprocessing, exploratory data analysis (EDA), and model optimization techniques. Emphasis is placed on practical implementation using popular libraries, including Pandas, NumPy, Scikit-learn, TensorFlow, and Keras.

Key highlights include:

• Practical examples and coding exercises for better understanding.

• Hands-on projects to build predictive models for business insights.

• Guidance on integrating machine learning models into production.

• Learn BI tool like Power BI for Data Visulaization.

• Learn SQL for Database manipulation

By the end of the program, students will have a solid foundation in data science and machine learning, empowering them to pursue roles such as Data Analyst, Machine Learning Engineer, or AI Specialist.

By the end of this course, you'll be able to:

• Master the core concepts of Data Science, Machine Learning, and Artificial Intelligence.

• Develop proficiency in Python programming for data analysis and visualization.

• Explore essential libraries like NumPy, Pandas, Matplotlib, and Scikit-learn.

• Perform data cleaning, preprocessing, and feature engineering.

• Build and evaluate predictive models, including linear regression, decision trees, and neural networks.

• Understand model deployment strategies and work with real-world datasets.

• Gain hands-on experience through projects and case studies.

• Learn SQL to manipulate database data
• Learn Power BI for Data visualization and Business Intelligence