PG Diploma in Advanced Data Engineering
Advance your career to the highest level of business leadership. Transform your expertise into strategic impact with our globally recognized program.
Duration: 8 Months
Format: Online
Accredited Program
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Doctor of Business Administration (DBA)
Advanced Your Career to the Highest Level of Business Leadership.
Duration: 2 Year
Format: Online
Accredited Program
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Start DBA Today
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Download Brochure
Get Course Details
Course Overview
PG Diploma in Advanced Data Engineering
The PG Diploma in Advanced Data Engineering is a comprehensive, industry-focused program designed to equip learners with the technical expertise required to build, manage, and scale modern data systems. The program focuses on practical, real-world applications of data engineering concepts used by leading organizations across industries.
Participants gain hands-on experience in data pipelines, ETL processes, data warehousing, cloud platforms, big data technologies, and data orchestration tools. The curriculum emphasizes performance, scalability, and reliability, enabling learners to design and maintain data architectures that support analytics, machine learning, and business intelligence initiatives.
The Changing Business Landscape
The Changing Business Landscape
The pace of change we are witnessing today is unlike anything we have seen in recent history.
Admission
Admission Requirements
General Admission Requirements
- A valid government-issued photo identity card.
- An updated resume outlining academic and/or professional experience
- Any document if not in English must be accompanied by a certified translated copy.
Additional Admission Requirements PG Diploma in Advanced Data Engineering
Applicants seeking admission to the PG Diploma in Advanced Data Engineering must have completed or be in the final year of a Bachelor’s degree in Computer Science, Information Technology, Engineering, Data Science, Mathematics, Statistics, or a closely related discipline from a recognized institution.
Candidates are expected to possess a foundational understanding of programming languages such as Python, SQL, or Java, along with basic knowledge of databases and data structures. Applicants are required to submit a completed application form, official academic transcripts, an updated resume, and a valid government-issued photo identification for verification purposes.
Prior professional experience in data engineering is not mandatory, as the program is designed to support both recent graduates and working professionals aiming to advance their technical expertise and career prospects in the data engineering domain.
Why Choose Us
Why choose PG Diploma in Data Engineering
The PG Diploma in Data Engineering is designed to prepare learners for the rapidly growing demand for professionals who can design, build, and manage large-scale data systems. As organizations increasingly depend on data to drive analytics, artificial intelligence, and strategic decision-making, data engineering has become a critical and high-impact career path. This program equips learners with practical, industry-relevant skills in data pipelines, cloud platforms, data warehousing, and big data technologies. With a strong emphasis on hands-on learning and real-world applications, the PG Diploma helps learners develop the technical expertise required to support modern data-driven environments.
Objectives
Program Objectives
The PG Diploma in Data Engineering is designed to develop advanced technical competence and practical expertise in the design, implementation, and management of scalable data systems. The program aims to prepare learners to address complex data challenges by applying industry-standard tools, cloud technologies, and data engineering frameworks in real-world business environments. The objective of the program is to enable learners to build reliable and efficient data pipelines, manage large-scale data architectures, and support analytics, artificial intelligence, and business intelligence initiatives. Through applied learning and hands-on projects, participants strengthen their analytical thinking, problem-solving abilities, and technical proficiency required to meet the evolving demands of data-driven organizations.
The program goals are:
- Goal 1: Develop strong expertise in designing, building, and managing scalable data pipelines and data architectures.
- Goal 2: Enable effective use of modern data engineering tools, cloud platforms, and big data technologies.
- Goal 3: Strengthen analytical and problem-solving skills for handling large, complex, and high-volume datasets.
- Goal 4: Engage in decision-making ethically and compassionately.
- Goal 5: Prepare learners for industry-ready roles by applying data engineering solutions to real-world business challenges.
Licensure & Associations
Course Structure
Program Curriculum
Module – 1 Structured Query Language
Introduction to SQL
- Database Normalization and Entity Relationship Model
- SQL Operators
- Join, Tables, and Variables in SQL
- Deep Dive into SQL Functions
- Subqueries in SQL
- SQL Views, Functions, and Stored Procedures
- User-defined Functions in SQL
- SQL Optimization and Performance
- SQL Parsing
- Managing Database Concurrency
- Introduction to NoSQL: MongoDB
Module – 2 Python Basics
- What is Python?
- Flowcharts, Data Types, Operations
- Conditional Statements & Loops
- Strings
- In-build Data Structures – List, Tuples, Dictionary,
- Set, Matrix Algebra, Number Systemx
- Basics of Time & Space Complexity
- OOPS
- Functional Programming
- Exception Handling & Modulex
- Python Libraries: Numpy, Pandas, Matplotlib, Seaborn, Plotly etc.
Module – 3 Big Data and Cloud Services
Big Data Frameworks
Hadoop
- HDFS
- YARN
- MapReduce
Apache Spark
- Spark core concepts: RDDs, DataFrames, and SparkSQL
- Parallel processing and distributed computing with Spark
- Spark for data transformation, aggregation, and analytics
- Powerful data processing with PySpark for scalable analytics
Distributed Databases
- CAP Theorem, consistency, availability, partition tolerance
- Cassandra, HBase: Columnar data stores for largescale datasets
Real-World Big Data Pipeline
- Design and implement a basic pipeline using Hadoop or Spark
- Data storage, transformations, and querying
Data Streaming
- Introduction to streaming data
- Apache Kafka: Basics
- Stream processing with Spark Streaming
Advance Cloud Services
AWS
- AWS EMR
- OnPrem vs Cloud
- HDFS vs S3
- What is S3
- EC2
- Elastic IP
- AWS storage, networking
- S3 and EBS
- AWS Glue
- AWS Redshift
Module – 4 ETL & Data Warehousing
- ETL Pipelines
- ETL concepts: Extract, Transform, Load
- Data ingestion and transformation
- Tools: Apache NiFi, AWS Glue
Data Warehousing
- Star Schema
- Snowflakes Schemas
- Introduction to cloud data warehouses: Redshift, Big Query
- OLAP vs OLTP
Module – 5 Advance Data Ops
- Advance Data Engineering
- High-availability and fault-tolerant designs
- Scalability Strategies
- DevOps for Data Engineering
- CI/CD Pilelines, Jenkins & Gitlab
- Infrastructure as Code: Terraform
- Containerization: Docker, Kubernetes
- Data Security
- Data Encryption
- Authentication and RBAC
Module – 6 DSA and System Design
Data Structures and Algorithms
- Arrays, hashmaps
- Stacks, queues
- Trees (binary trees, heaps)
- Graphs, sorting (QuickSort, MergeSort)
- Time and space complexity
System Design
- Scalable and fault-tolerant systems
- Data warehousing Design
- Scalable and fault-tolerant systems
- Data warehousing Design
More Information
Additional Information for PG Diploma in Data Engineering
FAQs
Frequently Asked Questions
What are the basic requirements of the PG Diploma in Data Engineering at Birchwood University?
Applicants to the PG Diploma in Data Engineering at Birchwood University must hold a Bachelor’s degree (or be in the final year) in Computer Science, Information Technology, Engineering, Data Science, Mathematics, Statistics, or a related discipline from a recognized institution. Candidates are required to submit an updated resume, a valid government-issued photo ID, and relevant academic documents (with certified English translations if applicable).
Do I need to visit University campus during the course of the program?
No. The PG Diploma in Data Engineering at Birchwood University is delivered fully online, so you are not required to visit the university campus at any stage. Students must, however, complete all prescribed coursework, assessments, and program requirements online to be awarded the PG Diploma.
How long is the PG Diploma in Data Engineering that Birchwood University offers?
The PG Diploma in Data Engineering at Birchwood University is designed to be completed in 8 months. The program follows a flexible online learning structure, allowing students and working professionals to balance their studies with other commitments.
What career opportunities are available after completing the Data Engineering program?
Graduates of the Data Engineering program can pursue a wide range of career opportunities across industries that rely on large-scale data systems. Common roles include Data Engineer, Analytics Engineer, Big Data Engineer, Cloud Data Engineer, ETL Developer, Data Platform Engineer, and Business Intelligence Engineer.
Is the Data Engineering program at Birchwood University worth it?
Yes. The PG Diploma in Data Engineering at Birchwood University is designed to equip learners with practical, industry-relevant skills that are in high demand in today’s data-driven job market. The program focuses on real-world applications, hands-on experience with data pipelines, cloud technologies, and scalable data architectures, preparing graduates for roles in data engineering, analytics, and related fields.
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