About
This comprehensive course is designed to take learners from basic to advanced levels in Data Science and Big Data Analytics. It covers a wide range of topics, from fundamental concepts to advanced techniques, providing a solid foundation for anyone looking to pursue a career in this field. By the end of the course, learners will have the knowledge and skills to understand and work on data science projects effectively. This course is designed to be practical and hands-on, with numerous examples and exercises to reinforce learning. By the end of the course, you will be well-equipped to tackle real-world data science and big data analytics projects with confidence. Chapter 1: Introduction to Data Science and Big Data Chapter 2: Basics of Data Chapter 3: Data Preprocessing Chapter 4: Introduction to Statistics Chapter 5: Data Visualization Chapter 6: Introduction to Programming for Data Science Chapter 7: Exploratory Data Analysis (EDA) Chapter 8: Introduction to Machine Learning Chapter 9: Supervised Learning Algorithms Chapter 10: Unsupervised Learning Algorithms Chapter 11: Model Evaluation and Validation Chapter 12: Advanced Machine Learning Techniques Chapter 13: Introduction to Big Data Technologies Chapter 14: Big Data Processing and Analysis Chapter 15: Data Warehousing and ETL Chapter 16: Cloud Computing for Data Science Chapter 17: Data Security and Privacy Chapter 18: Case Studies and Real-World Applications Chapter 19: Tools and Technologies for Data Science Chapter 20: Capstone Project