CAP Prep - Data Science
EDA using Python
Web Scraping /
Master the essential skills of SQL, advanced Excel, and different industrial business scenarios to excel in today's data-driven business world. Dive into SQL to efficiently manage and analyze data, mastering concepts like data modeling, querying, and stored procedures. Enhance your data analysis capabilities with advanced Excel techniques, including complex formulas, pivot tables, and data visualization. Then, explore diverse industrial business scenarios, such as supply chain management, retail merchandising, Fantasy gaming, healthcare operations, and financial analysis to understand their unique challenges and optimize operations.
Master the art of guesstimates and case studies to excel in business problem-solving. Learn how to make quick, educated estimates and analyze complex business scenarios using logical reasoning, data interpretation, and critical thinking. Develop skills to solve real-world business problems through case studies, examining market trends, competitive landscapes, and strategic decision-making. Enhance your problem-solving abilities and demonstrate your analytical prowess in guesstimates and case study interviews and assessments.
Learn how to create interactive dashboards, reports, and visualizations using Power BI's intuitive interface and powerful features. Dive deeper into SQL with advanced querying techniques, such as subqueries, joins, and window functions, to extract, transform, and analyze data efficiently. Combine the capabilities of Power BI and advanced SQL to gain valuable insights from complex datasets and present them in a compelling and impactful way.
Harness the power of Python as a versatile programming language for web scraping and SQL. Learn Python fundamentals, data manipulation, and automation. Extract data from websites using BeautifulSoup and Selenium. Expand your coding skills and data processing capabilities with Python's wide range of applications.
Dive into the fundamentals of Machine Learning and Gen AI. Learn the key concepts, algorithms, and techniques behind Machine Learning, including supervised and unsupervised learning, regression, classification, and clustering. Understand how to train and evaluate ML models using popular libraries like scikit-learn and TensorFlow. Explore the exciting field of Gen AI, which combines genetic algorithms and artificial intelligence to optimize solutions and make intelligent decisions. Develop a strong foundation in Machine Learning and Gen AI to unlock their potential in various domains and applications.
Learn how to analyze data, perform statistical tests, and visualize insights using libraries like NumPy, Pandas, and Matplotlib. Dive into probability theory and its practical applications, understand exploratory data analysis techniques, apply statistical methods to draw meaningful conclusions, and create compelling visualizations to communicate data-driven stories. Enhance your data analysis skills and gain a deeper understanding of data through Python's powerful ecosystem.
Module - 1
Module - 2
Module - 3