Call: +92 371 022 0410

Data Engineering

Neural networks, CNNs, RNNs, transfer learning, and production best practices for deep learning.

Intermediate Level
Data Engineering

What You'll Learn

  • Batch vs Streaming Concepts
  • Data Lakehouse Basics
  • ETL vs ELT

  • Star and Snowflake Schemas
  • Dimensional Modeling
  • Normalization vs Denormalization

  • Orchestration and Scheduling
  • Idempotency and Backfills
  • Data Quality and Observability

  • Storage and Compute Options
  • Messaging and Queues
  • Data Processing Engines

  • Advanced SQL Patterns
  • Python for ETL and Automation
  • DataFrames and Serialization

  • Introduction to NLP
  • ANN and key characteristics
  • Tokenization and Text Cleaning
  • Stemming and Lemmatization
  • Parsing and Syntax Trees

What You'll Achieve

This course is designed to give you practical skills and knowledge that employers value

Design batch and streaming data pipelines end-to-end
Model data for analytics and governance
Automate ETL/ELT workflows with Python and SQL
Operate on-premise and cloud-native data tools
Implement observability and reliability basics

Prerequisites

Basic programming knowledge and familiarity with mathematics/statistics.

Important Dates

Course Launch

Coming Soon

Application Window

TBA

Course Information

Duration: Coming Soon
Schedule: Coming Soon
Fee: TBA
Level: Intermediate Level
Course Features
Expert Instructors
Learn from industry professionals with years of practical AI experience
Hands-on Projects
Work on real-world projects to build your portfolio and gain practical experience
Industry Recognition
Earn certificates recognized by leading Canadian tech companies and employers globally
Career Support
Get job placement assistance and career guidance throughout your journey