About the Program
Data Engineering Tools encompass a suite of technologies and frameworks essential for the effective management, processing, and analysis of extensive datasets. Within this domain, data engineers play a pivotal role, tasked with the design and upkeep of intricate data pipelines, ensuring the reliability and accessibility of critical information. Their expertise is fundamental in enabling data-driven decision-making and bolstering a diverse range of data-intensive applications, ranging from business intelligence platforms to advanced machine learning algorithms. This specialized skill set is highly sought after in today's data-centric landscape, making data engineers invaluable assets in the IT industry.
Courses
    Credits Semester
  • Hadoop Eco System with HDFS and MapReduce 3 III
  • Data Processing with Hive and Pig Latin 3 IV
  • Complete Python for Data Engineers 3 V
  • PySpark for Data Engineers 3 V
  • Cloud Data Engineering AWS, GCP, and Azure 3 VI
  • Real-Time Data Engineering with Streaming Tools 3 VII
  • Project Work - The Data Services Capstone: Exploring Big Data Tools 3 VIII
    Credits Semester
  • IT World Essentials: Your Digital Entrypoint 3 I
  • Critical Thinking, Design Thinking, Leadership and Teamwork 3 II
  • Project Work - The Data Services Capstone: Exploring Big Data Tools 3 VIII
    Credits Semester
  • Critical Thinking, Design Thinking, Leadership and Teamwork 3 II
  • Career Readiness in Digital Era 3 VI
Mode of Delivery
  • Self-paced learning – 10 hours
  • VILT sessions – 28 hours
  • Project work – 7 hours
  • Face-to-face instructor led sessions / VILT sessions (including project work) – 45 hours
  • Self-paced learning + Expert session – 30 hours
  • Project work – 15 hours
Job Roles
  • Data Engineer
  • Data Integration Engineer
  • Big Data Analyst
Software Tools
  • Python
  • Scala
  • Presto
  • Hive
  • Pig
  • Flink
  • Zeppelin
  • Oozie
  • kafka
  • Pyspark
  • Databricks
  • MySQL
  • Cassandra
  • MongoDB
  • Hadoop
  • Airflow
  • Spark
  • Ambari
  • Zookeper
  • Flume
  • Sqoop
Skills
  • Designing efficient and scalable data structures for modeling and analysis.
  • Working with NoSQL databases like MongoDB and Cassandra for unstructured data.
  • Implementing centralized data storage solutions in data warehousing for large datasets.
  • Utilizing Hadoop and Spark for big data processing and distributed computing.
  • Combining data from multiple sources for seamless integration into a unified system.
  • Managing large datasets effectively with Hadoop and Spark ecosystem for performance.