This course demystifies core data science concepts and techniques through engaging Python lessons and real datasets. You’ll gain practical experience working with the Python ecosystem, including pandas, NumPy, scikit-learn, and more, as you analyze authentic data and build meaningful applications from scratch. From setting up your programming environment to building your first … [Read more...] about Data Science Fundamentals Part 1: Unit 1
Data Analysis
PySpark: Apply & Evaluate Predictive ML Models
This intermediate-level course empowers learners to apply, analyze, and evaluate machine learning models using Apache PySpark’s distributed computing framework. Designed for data professionals familiar with Python and basic ML concepts, the course explores real-world implementation of both regression and classification techniques, along with unsupervised clustering. In Module … [Read more...] about PySpark: Apply & Evaluate Predictive ML Models
Data Science Fundamentals, Part 2
Master essential concepts, theory, and hands-on techniques to become an effective data scientist. Guided by real-world case studies and applied Python programming, you'll learn to acquire, analyze, and model complex datasets, drawing actionable insights using industry-standard tools like pandas, NumPy, SciPy, and scikit-learn. Confidently tackle data problems, apply machine … [Read more...] about Data Science Fundamentals, Part 2
Data Science Fundamentals Part 1: Unit 2
This course dives into real-world data sourcing, including making web requests, web scraping, and integrating diverse data types from APIs, files, and databases. You'll learn to parse and structure data in formats like XML and JSON, and leverage object-oriented programming to create robust data models. By the end of the course, you’ll be equipped to efficiently acquire, … [Read more...] about Data Science Fundamentals Part 1: Unit 2
Spark and Python for Big Data with PySpark
This specialization provides a complete learning pathway in Apache Spark and Python (PySpark) for big data analytics, machine learning, and scalable data processing. Learners will begin with foundational Python and PySpark techniques, advance to predictive modeling and clustering, and explore advanced data workflows including ETL pipelines, streaming, and real-time … [Read more...] about Spark and Python for Big Data with PySpark
