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Become an In-Demand Data Engineer. Stop learning theory—start building. This course empowers you to process massive datasets—social, market, and transactional—using industry-standard tools. Gain hands-on expertise in RDBMS, NoSQL, and Cloud technologies, learning to craft powerful data pipelines with Python. By the end, you’ll be fully equipped to integrate, cleanse, and analyze data, making you a proactive and productive asset in any enterprise.
3 Months
23 +
Online/Offline
Learn the skills required to handle business events, business transactions, social data, and market data sets. You will be empowered to understand and work with RDBMS, NoSQL, and cloud file storage data. You will be processing the data sets based on the application requirement using Python and its libraries. You can build data pipelines in an enterprise to analyze the data, integrate the data, cleanse and handle the exception data with ease. You can be proactive and productive in any company you work for as a Data Engineer.
• Introduction to Business
• Industries and Business Characteristics
• Approach to learn anything in business
• Horizontal and Verticals in Industries
• Industry to Information
• Understanding Business Process
• High Level View of a Company / Organization
• Introduction to RDBMS
• What is Data?
• Databases
• Types of Databases
• Relational DBMS
• Entities and Relationships
• Tables in RDBMS
• Primary Key, Foreign Key,EF Codd’s Rules
• What is a transaction
• ACID property
• Introduction to Python
• Basic Python Syntax
• String Handling
• Operators
• Conditional Statements
• Looping Statements
• Control Statements
• Collections
• Functions
• Modules
• Packages
• File Handling
• OOPS Concepts
• Classes and Objects
• Inheritance and Polymorphism
• Abstract classes and Interfaces
• Exception Handling
• Regular Expression
• Database Connectivity
• Python XML and JSON Parsers
• Introduction to Pandas
• Handling DataFrame
• Merge and Groupby
• Pivot table and Stack Unstack
• Time Series analysis
• Numpy
• Data Visulization
• Introduction to PowerBI
• PowerBI Desktop Interface
• Connecting Power BI to excel
• Charts and thier properties
• Table,matrix properties, Tree Map
• Introduction to DAX,Derived Fields and Date functions
• Introduction to conditional statements
• Slicers and its basic uses properties
• Super aggregations and Scatter plot
• Introduction to rank and Parameter
• Introduction to Power BI Service,Row Level Security
• Time intelligence functions YTD,QTD,MTD
• Date ADD, Same period, Parallel Period
• Introduction to cloud computing
• Overview of an AWS free tier offer
• Creating an AWS account
• Intoduction to EC2 service
• Launching Windows and linux instances
• Connecting to windows and linux instances
• Introduction to S3
• Creating Buckets and uploading object to a Bucket
• S3 bucket policy
• Introduction to RDS
• Launching Oracle Database server
• Connecting to Oracle database
• Introduction to IAM
• Creating users and attaching services to a user
• File commands
• Dir commands
• Vi editor
• Linux process
• Grep and its options
• Shell scripting & awk
• Cron job scheduling
A capstone project is a culminating and often multifaceted project undertaken at the end of an academic program or training, It allows students to apply the knowledge and skills they’ve acquired throughout their studies to solve a real-world problem or address a specific challenge. Capstone projects can vary widely in scope and format, ranging from research papers and presentations to software development, design prototypes, or even community service initiatives. They serve as a practical demonstration of a student’s readiness for graduation or entry into their chosen field.
Having 25+ years of experience in the IT industry. Empowering jobseekers to become good employees who work effectively at every opportunity.
Data Engineering involves designing, building, and maintaining data pipelines and infrastructure that enable organizations to collect, process, and analyze large volumes of data efficiently.
This course is suitable for graduates, software developers, data analysts, database professionals, IT professionals, and anyone interested in building a career in Data Engineering.
Basic knowledge of programming and SQL is helpful but not mandatory. The course starts with fundamentals and gradually covers advanced concepts.
You’ll learn SQL, Python, ETL, Data Warehousing, Apache Spark, Hadoop, Kafka, Airflow, Cloud Platforms (AWS/Azure/GCP), and real-world data pipeline development.
Yes. The curriculum includes practical assignments, case studies, and industry-level projects to help you gain real-world experience.
Yes. The course is designed for both beginners and professionals looking to upskill or transition into Data Engineering.
After successfully completing the course, you’ll receive an industry-recognized Data Engineering certification from I Bridge 360.
Yes. I Bridge 360 offers placement assistance, including resume building, mock interviews, career guidance, and interview preparation.
You can apply for roles such as Data Engineer, ETL Developer, Big Data Engineer, Cloud Data Engineer, Data Platform Engineer, and Analytics Engineer.
Yes. The course covers cloud-based data engineering concepts using leading platforms such as AWS, Microsoft Azure, or Google Cloud.
The course duration typically ranges from 3 to 4 months, depending on the chosen learning schedule.
Yes. I Bridge 360 offers live instructor-led training along with recorded sessions for revision and flexible learning.
Absolutely. You’ll build end-to-end data engineering projects that simulate real business scenarios and strengthen your portfolio.
I Bridge 360 offers an industry-focused curriculum, experienced trainers, hands-on projects, personalized mentorship, certification, interview preparation, and placement assistance to help learners launch successful careers in Data Engineering.
