Big Data, PySpark, AWS, Scala & Data Scraping – Complete Online Course
Course Description
This comprehensive, hands-on course is designed to take you from beginner to advanced in key technologies used across modern data engineering, big data processing, automation, and applied machine learning. You’ll learn how to scrape, mine, process, analyze, and manage massive datasets using Python, Scrapy, Scala, PySpark, AWS, and MongoDB—while also gaining the practical skills needed to build real-world data pipelines and AI-powered applications.
The curriculum covers everything from the fundamentals to advanced workflows, ensuring you can confidently apply concepts through live coding, quizzes, homework, and hands-on projects. Each module introduces essential theory and immediately reinforces it with real implementations, helping you bridge the gap between learning and doing.
By the end of this course, you'll be equipped to build scalable big data solutions, perform intelligent data extraction, engineer data pipelines, and implement machine learning workflows using state-of-the-art tools and cloud platforms.
What You’ll Learn
Core Technical Skills
Big Data fundamentals with Scala, Spark, PySpark, and AWS
Data scraping and mining from beginner to pro using Python, Scrapy, BS4, and Selenium
NoSQL data processing with MongoDB, including CRUD, operators, and integrations with Node, Python, PySpark, and Django
Building AI-powered applications and machine learning workflows
Constructing complete ETL pipelines using Spark and AWS services
End-to-End Practical Applications
Cleanly unfolding concepts with simple explanations and real examples
Every theory topic is followed by hands-on coding
Multiple projects and mini-projects for Scala, Spark, PySpark, data scraping, and MongoDB
Trial-and-error learning with guided solutions, quizzes, and practice tasks
Requirements
Basic understanding of HTML, Python, SQL, and Node.js
No prior knowledge of Scala or data scraping is required
Basic programming familiarity and a willingness to learn by doing
Commitment to practicing live coding to reinforce concepts
Course Modules
I. Scala for Big Data
Learn variables, data types, functions, classes, and data structures
Explore Scala’s role in big data engineering
Work with Hadoop and Spark using Scala
Hands-on Scala Spark project + 6 mini-projects
Understand RDDs, DataFrames, MapReduce, and distributed processing
II. PySpark & AWS
Build end-to-end data analysis workflows with PySpark
Master RDDs, DataFrames, transformations, and actions
Explore Spark SQL and the Spark ecosystem
Work in Databricks for scalable distributed computing
Learn how Spark communicates with AWS storage, compute & databases
Implement ETL pipelines using AWS S3, Spark, and downstream systems
III. Data Scraping & Data Mining (Beginner → Professional)
Learn browser–server interactions, HTTP requests, synchronous/asynchronous flows
Use Requests, BeautifulSoup, Scrapy, and Selenium
Build scraping bots, automate website extraction, and handle APIs
Hands-on labs + 4 real-world scraping projects
Understand how to mine structured/unstructured website data
Learn error handling, parsing, and scraping best practices
IV. MongoDB – NoSQL for Modern Applications
CRUD operations, query operators, projection, and update operators
Create clusters on MongoDB Atlas
Work with MongoDB using Node, Python, Django, and PySpark
Build CRUD APIs with Django + MongoDB
Implement ETL pipelines using Spark to load data into MongoDB
Understand why MongoDB is essential for large-scale data systems
Skills You Will Be Able to Apply
Collect, clean, analyze, and manage large datasets
Build automated scraping pipelines for real-world products, websites, and APIs
Implement Spark-based ETL pipelines on AWS
Build data-driven apps with MongoDB and Python
Design AI-powered applications using collected and processed data
Translate complex concepts into production-quality data solutions
Who This Course Is For
Absolute beginners wanting a full-stack data engineering pathway
Developers and aspiring data engineers
Data scientists and ML practitioners needing big data skills
Professionals who want to learn by doing
Drop shippers, analysts, and entrepreneurs wanting smart, automated solutions
Anyone who enjoys theory paired with real-world practical implementation