PGCP-BDA Course Overview & Industry Relevance
The Post Graduate Certificate Programme in Big Data Analytics (PGCP-BDA) (Course ID: 65, formerly PG-DBDA) equips engineers with skills to design and manage distributed data systems.
Delivered over 24 weeks full-time, the programme emphasizes distributed computing frameworks like Apache Hadoop, Apache Spark, and enterprise cloud data warehousing.
Curriculum Modules
| Module Code | Module Title | Key Competencies |
|---|---|---|
| MOD-01 | Linux Programming & Cloud Computing | Linux Administration, Cloud Storage, Distributed Architecture |
| MOD-02 | Python & R Programming | Scripting, Data Wrangling, Statistical Programming |
| MOD-03 | Java Programming | Object-Oriented Fundamentals, I/O Streams, Concurrency |
| MOD-04 | Data Collection & DBMS Platforms | SQL, Schema Modeling, Data Warehousing, NoSQL Stores |
| MOD-05 | Advanced Analytics using Statistics | Probability, Hypothesis Testing, Regression Models |
| MOD-06 | Big Data Technologies | Hadoop HDFS, MapReduce, Apache Spark, Kafka Streaming |
| MOD-07 | Practical Machine Learning | Supervised/Unsupervised Modeling, Feature Engineering |
| MOD-08 | Data Visualization & Reporting | Dashboards, Power BI, Tableau, Analytical Communication |
| MOD-09 | Aptitude & Communication | Reasoning, Problem Solving, Presentation Skills |
| MOD-10 | Capstone Big Data Project | Distributed Pipeline Implementation & Viva Voce |
Big Data Technologies: Hadoop & Spark
- Hadoop Ecosystem: Distributed file systems (HDFS), cluster management with YARN, MapReduce concepts
- NoSQL & Columnar Storage: High-throughput data storage, partitioning, querying large datasets
- Distributed Messaging: Apache Kafka architecture, producers, consumers, stream ingestion
- Apache Spark & PySpark: Resilient Distributed Datasets (RDDs), Spark DataFrames, Spark SQL, stream processing
Data Collection, DBMS & Statistical Modeling
- Data Warehousing: Fact and Dimension tables, Star and Snowflake schemas, ETL pipeline design
- Advanced SQL: Window functions, CTEs, indexing, query optimization
- Statistical Analytics: Hypothesis testing, ANOVA, linear regression models, logistic classification
❓ Frequently Asked Questions
What is the course duration of CDAC PGCP-BDA?
PGCP-BDA is conducted as a 24-week full-time intensive programme covering data engineering, distributed computing, and practical analytics.
Does PGCP-BDA require prior programming knowledge?
Basic programming understanding is helpful, but the course includes foundational modules in Linux, Python, and Java from the start.
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Practice Mock Tests with Real C-CAT Pattern
Prepare with exam-level timer, negative marking simulation (−0.25 penalty), and section-wise analytics built by Sunbeam toppers.
Topics:#PGCP-BDA#Big Data#Apache Spark#Hadoop#Data Analytics#Python