Pre-requisite: IT Professionals with Python Coding and SQL/Database Experience with Good Communication Skills.

Job Prospects: DATA ENGINEER / CLOUD DATA ENGINEER / PYTHON DEVELOPER / AUTOMATION ENGINEER / MACHINE LEARNING (ML) - ARTIFICIAL INTELLIGENCE (AI) ENGINEER.

COURSE-1: Python Programming-Intermediate Level (12 Sessions)

MODULE-1: INTRODUCTION TO PYTHON 

• Introduction and History of Python
• Various Python Distribution Vendors & Text Editors
• Python Installation (Windows, Mac, Linux)
• Introduction to Jupyter Notebook
• Exercise

MODULE-2: VARIABLE AND DATA TYPES

• Operators and Order of Operations
• Naming and Using Variables
• Data Types (Strings, Numbers)
• Working, Concatenation, and Conversion of Strings
• String Operations
• Expression, Comments, Using the Input() function
• Exercise

MODULE-3: DATA STRUCTURES: LISTS & SETS

• Create a List
• List of Lists
• Subsetting Lists
• Manipulating Lists
• Delete List Elements
• Inner working of Lists
• Slicing and Dicing
• Properties of Sets
• Access to Sets
• Manipulating Sets
• When to use Sets
• Exercise

MODULE-4: DATA STRUCTURES: TUPLES & DICTIONARIES

• Understanding of Immutability Nature
• Creating a Tuple
• Access Tuples
• When to Use Tuples
• Idea Behind Dictionaries
• Create a Dictionary
• Access a Dictionary
• Dictionary Manipulations
• Dictionaries to Data Frames
• Exercise

MODULE-5: CONDITIONAL STATEMENTS AND LOOPS

• IF, IF-ELSE, IF-ELIF-ELSE Statements
• Multiple Conditions and Multiple IF Statements
• WHILE and FOR Loops
• Nesting Loops
• Break Command and Avoiding Infinite Loops
• Understanding Iterators
• Applying Iterators on Data Structures
• Exercise

MODULE-6: FUNCTIONS AND EXCEPTIONS HANDLING

• Methods and Functions Overview
• Defining and Calling Functions
• Returning a Value & Modules
• Working with Functions and Comprehensions
• Lambda Expressions, Map and Filter Functions
• Handle Possible Errors
• Exception Handling (Try-except, Try-except-finally, etc.)
• Exercise

MODULE-7: PROGRAMMING ALGORITHMS

• Algorithm Basics
• Search
• Sort
• Factorial
• Even or Odd
• Target Sum
• Print Pattern
• Recursion
• Time Complexity
• Two Pointer           

MODULE-8: DATA ANALYSIS (NumPy and Pandas)

• Data Analysis Introduction
• Data Analysis using Pandas
• Pandas Series
• Pandas Data Frames
• Manipulating Data in Data Frames
• Exercise 

MODULE-9: DATA VISUALIZATION

• Introduction to Matplotlib
• Installation of Matplotlib
• Plotting Line Graphs, Histograms, Bar Charts, Scatter plots and more
• Exercise

MODULE-10: OBJECT-ORIENTED PROGRAMMING

• Object Oriented Programming
• Defining Classes and Objects
• Defining Methods
• Inheritance and Polymorphism
• Exercise

COURSE-2: Cloud Infrastructure (4 Sessions)

MODULE-1: INTRODUCTION TO AMAZON WEB SERVICES (AWS)

• Cloud Providers (AWS, AZURE, GCP, etc.)
• Cloud Computing
• AWS Cloud Services
• Virtual Private Cloud (VPC)
• Exercise

MODULE-2: AWS SETUP, INSTALLATION AND CONFIGURATION

• Elastic Compute Cloud (EC2) Instance Setup (Python / Java Installation) / File Transfer
• EMR (Cluster) Setup for Big Data Processing
• Relational Database Service (RDS) Setup 
• Connection using WinSCP and Putty
• S3 Bucket
• Exercise

COURSE-3: Data Engineer (8 Sessions)

MODULE-1: INTRODUCTION TO DATA ENGINEERING

• What is Data Engineering
• Roles of a Data Engineer
• Tools of Data Engineering

MODULE-2: RELATIONAL Vs NoSQL

• Databases and Design
• SQL vs NoSQL (MY SQL vs MongoDB)
• Pandas vs SQL
• Database Schemas
• Exercise

MODULE-3: APPLICATION PROGRAMMING INTERFACE (API)

• What is API
• Building an API
• Storing data in MySQL and MongoDB.

MODULE-4: APACHE SPARK

• Introduction Apache Spark Framework
• Reasons to move with Spark Framework.
• Spark installation on AWS
• Spark-Submit job with Word Count Program
• Running Programs using Pyspark vs Spark Framework
• Exercise

MODULE-5: PYSPARK

• Introduction to PySpark
• Work with PySpark on the Spark Framework
• Working on Data Set on Spark Framework with PySpark
• Exercise

MODULE-6: APACHE KAFKA

• Introduction to Kafka
• Data Delivery and Stream Processing
• Project Structure and Running Samples on the EMR Cluster
• Exercise

SELF-STUDY

• Databases and SQL
• JavaScript, HTML, and CSS
• Agile Software Development

• Live Training with Demos
• Practical Assignments & Assessments
• Real-Time Scenarios
• Communication Skills Guidance*
• Effective Resume Building*
• Interview Preparation / Mock Interview*
• Placement Assistance*

Classes: 35-40 Hours

Assignments: 40+ hours