Career Objective
To provide a comprehensive understanding of shell scripting and GIT basics.
To introduce students to the Linux environment and scripting basics and to cover text and file processing in Linux.
To teach process management and advanced topics in Linux, including cron jobs and scheduling.
What you will learn?
Master Data Processing
- Learn to work with various data processing technologies such as Apache Hadoop, Apache Spark, and Apache Kafka.
- Understand how to design, build, and maintain scalable data pipelines.
Database Management
- Gain proficiency in database management systems (DBMS) including SQL and NoSQL databases.
- Learn to optimize database schemas for performance and scalability.
Data Warehousing
- Explore concepts and tools related to data warehousing, including ETL (Extract, Transform, Load) processes, data modeling, and dimensional modeling.
- Understand how to design and implement data warehouses for analytical purposes.
Big Data Technologies
- Understand how to design and implement data warehouses for analytical purposes.
- Learn to process and analyze large volumes of data efficiently.
MODULE SEQUENCE TO BE FOLLOWED:
This course includes:
- 40 hours on-demand videos
- Interesting Quizes for every module
- Individual certificates
- Provide Badges
- App Accessissibility
- Full Time Access
- Feedback Mechanism
- Downloadable Materials
- Resource Library
Frequently Asked Questions
This course is ideal for aspiring data engineers, software engineers looking to specialize in data, data analysts transitioning into engineering roles, and anyone interested in mastering data infrastructure and processing technologies.
Basic programming skills (preferably in Python, Java, or similar languages) and familiarity with databases and SQL are recommended. Understanding fundamental data concepts such as data types, data structures, and data manipulation is beneficial but not mandatory.
The course is structured into modules covering essential topics such as data processing technologies, database management, data warehousing, big data technologies, cloud data engineering, and data pipeline orchestration. Each module includes lectures, hands-on exercises, and projects to reinforce learning.
You will need access to a computer with internet connectivity. Specific tools and software such as Apache Spark, databases (e.g., PostgreSQL, MongoDB), and cloud platforms (e.g., AWS, GCP) will be introduced and utilized throughout the course.
Yes, upon successful completion of the course and projects, you will receive a certificate of achievement. This certificate validates your proficiency in data engineering concepts and practical skills.
