Big Data Analytics Certification: From Fundamentals to Forecasting
Big Data Analytics: From Fundamentals to Forecasting is a fast-paced, career-ready certification program designed to equip learners with essential skills in managing, analyzing, and interpreting large-scale datasets. From Hadoop to Spark, data wrangling to predictive analytics — this program gives you a competitive edge in the booming data landscape.
By combining foundational theory with hands-on projects, this course ensures you're not just learning tools, but also applying them in real-world business contexts — across domains like finance, logistics, and consumer tech.
Who Is It For?
This course is ideal for:
Aspiring data engineers, analysts, or data scientists
Professionals working in IT, analytics, or data roles seeking upskilling
Students from STEM backgrounds looking to break into Big Data roles
Business professionals interested in advanced data-driven strategies
What Will You Get?
Full-stack Big Data Training: Hadoop, Spark, HDFS, Hive, NoSQL (MongoDB)
Project-Based Learning: Real-world use cases in large data environments
Code & Query Practice: Exercises and datasets for hands-on work
Mentor Support: Expert sessions and doubt-clearing
Soft Copy of Certification: Shareable on LinkedIn and your CV
Post-Certification Benefits:
Job-Ready Portfolio: Showcase real-world data pipelines, queries, and analytics projects
Resume & LinkedIn Boost: Certification from a reputed edtech platform adds credibility
Confidence for Interviews: You’ll have practical tools and knowledge of industry-used Big Data stacks
TOC: Curriculum Overview
Module 1: Introduction to Big Data
What is Big Data?
5Vs of Big Data
Big Data Analytics vs Traditional Analytics
Module 2: Big Data Ecosystem
Overview of Hadoop, Hive, NoSQL, File Formats & Compression techniques, Scala basics, Spark, and HDFS
Roles in the Big Data world: Analyst vs Engineer vs Scientist
Module 3: HDFS & Hadoop Basics
Understanding Distributed File Systems
HDFS Architecture
MapReduce Concepts (Simplified for Analysts)
Module 4: Hive for Data Querying
HiveQL Basics
Joins, Filters, and Aggregations
Running Queries on Sample Datasets
Module 5: Data Wrangling at Scale
Cleaning and transforming large datasets
Using PySpark for basic data operations
Data ingestion & preprocessing
Module 6: Apache Spark for Analysts
Introduction to Spark architecture
RDDs vs DataFrames
Hands-on with Spark SQL
Module 7: NoSQL
Key-Value Stores vs Relational Databases
Module 8: Case Studies & Capstone Projects
Real-life datasets from Telecom, Retail, Logistics
Group/individual projects with evaluation
Mentor feedback & presentation prep
Certification:
You will receive a digital certificate upon course completion that you can showcase on LinkedIn, add to your resume, or share with employers.
Course Duration & Schedule:
🗓 Total Duration: 16 Days
🕒 Schedule: Weekend Only
📅 Timings: Saturday & Sunday – 2 Hours per Day
📍 Mode: Live Online Classes (Interactive + Mentor-led)