AI (ARTIFICIAL INTELLIGENCE)

Course Description: This comprehensive course on Data Science with Python is designed for learners at all levels, from beginners with no prior coding experience to advanced learners looking to deepen their data science expertise. The course covers the full spectrum of skills needed to become proficient in data science, guiding students from the basics of Python programming to advanced data science techniques and applications.

Learning Outcomes:

By the end of this course, students will:

• Master Python programming from the basics, including data types, loops, functions, and libraries.
• Develop a strong foundation in essential libraries for data science, including NumPy, Pandas, and Matplotlib, and use them for data manipulation and visualization.
• Understand and apply key statistical concepts essential for data science, such as probability, regression, and hypothesis testing.
• Perform data cleaning, transformation, and exploratory data analysis on real-world datasets.
• Use advanced Python libraries like Scikit-learn and TensorFlow for machine learning and deep learning applications.
• Build, evaluate, and optimize machine learning models, including classification, regression, clustering, and recommendation systems.
• Gain hands-on experience in project-based learning through end-to-end data science projects, from data collection and preprocessing to model building and deployment.
• Acquire the skills to work with large datasets, implement model performance improvement strategies, and deploy models in real-world scenarios.