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Python & PySpark Training Syllabus

Python Programming

From Beginner to Advanced - Complete Learning Path

Module 1: Python Fundamentals

4 hours

Introduction to Python 30 minutes

What You Will Learn:

  • Understand what Python is and why it's popular
  • Explore Python's applications across different domains
  • Learn about Python's key features and advantages
Resources: Free MCQ Test & Interview Questions Available

Installation & Setup 45 minutes

What You Will Learn:

  • Install Python on Windows, Linux, and Mac systems
  • Configure environment variables properly
  • Explore different Python IDEs and choose the right one
Resources: Free MCQ Test & Interview Questions Available

Variables & Basic Operations 1 hour

What You Will Learn:

  • Declare variables following Python conventions
  • Use comments and proper indentation
  • Work with different data types and built-in functions
  • Take user input and display output
Resources: Free MCQ Test & Interview Questions Available

String Operations 1 hour

What You Will Learn:

  • Manipulate strings using built-in methods
  • Apply slicing and indexing techniques
  • Use negative indexing for efficient string access
  • Perform mathematical operations on strings
Resources: Free MCQ Test & Interview Questions Available

Module 2: Python Programming Concepts

5 hours

Operators in Python 1.5 hours

What You Will Learn:

  • Use arithmetic, assignment, and comparison operators
  • Implement logical and bitwise operations
  • Apply membership and identity operators
  • Combine different operators in expressions
Resources: Free MCQ Test & Interview Questions Available

Decision Making & Control Flow 1.5 hours

What You Will Learn:

  • Implement if, if-else, and if-elif-else statements
  • Use ternary operators for concise conditional logic
  • Control program flow with loops and recursion
  • Apply break, continue, and pass statements
Resources: Free MCQ Test & Interview Questions Available

Data Structures 2 hours

What You Will Learn:

  • Work with lists, tuples, dictionaries, and sets
  • Apply packing, unpacking, and zip operations
  • Use list, dictionary, and set comprehensions
  • Manipulate data structures with built-in methods
Resources: Free MCQ Test & Interview Questions Available

Module 3: Advanced Python Concepts

6 hours

Functions & Functional Programming 2 hours

What You Will Learn:

  • Create and use functions with different argument types
  • Implement lambda functions and higher-order functions
  • Use map(), filter(), and reduce() functions
  • Work with generators, iterators, and decorators
Resources: Free MCQ Test & Interview Questions Available

Python Modules & Regular Expressions 2 hours

What You Will Learn:

  • Import and use standard library modules
  • Create and import your own modules
  • Implement regular expressions for pattern matching
  • Use wildcards and meta characters effectively
Resources: Free MCQ Test & Interview Questions Available

File Handling & Logging 2 hours

What You Will Learn:

  • Read from and write to files in Python
  • Work with CSV files for data processing
  • Implement logging with different levels and handlers
  • Format log messages and save to files
Resources: Free MCQ Test & Interview Questions Available

Module 4: Python in Practice

5 hours

Database Operations 1.5 hours

What You Will Learn:

  • Connect to SQLite databases from Python
  • Execute SQL queries and handle transactions
  • Use cursors for database operations
  • Implement commit and rollback operations
Resources: Free MCQ Test & Interview Questions Available

Object-Oriented Programming 2 hours

What You Will Learn:

  • Create classes and objects in Python
  • Implement inheritance and polymorphism
  • Use class methods and static methods
  • Apply operator overloading and access modifiers
Resources: Free MCQ Test & Interview Questions Available

Error & Exception Handling 1.5 hours

What You Will Learn:

  • Handle exceptions using try-except blocks
  • Create custom exception classes
  • Implement proper error messaging
  • Use finally and else clauses in exception handling
Resources: Free MCQ Test & Interview Questions Available

PySpark & Big Data Processing

Scalable Data Processing with Apache Spark

Module 5: Spark Fundamentals

4 hours

Spark Basics & Architecture 2 hours

What You Will Learn:

  • Understand Spark architecture and components
  • Explore Spark's history and evolution
  • Work with Spark Shell and PySpark
  • Learn about lazy execution and DAGs
Resources: Free MCQ Test & Interview Questions Available

RDDs (Resilient Distributed Datasets) 2 hours

What You Will Learn:

  • Create and manipulate RDDs
  • Apply transformations and actions
  • Work with partitions and understand data distribution
  • Implement caching and persistence strategies
Resources: Free MCQ Test & Interview Questions Available

Module 6: Advanced Spark Concepts

5 hours

DataFrames & Spark SQL 2.5 hours

What You Will Learn:

  • Create and manipulate DataFrames
  • Convert between RDDs and DataFrames
  • Work with schemas and different data formats
  • Execute SQL queries on Spark data
Resources: Free MCQ Test & Interview Questions Available

Spark Streaming & Advanced APIs 2.5 hours

What You Will Learn:

  • Implement real-time data processing with Spark Streaming
  • Work with DStreams for continuous data
  • Use Dataset API for type-safe operations
  • Handle stateful stream processing
Resources: Free MCQ Test & Interview Questions Available

Python Use Cases

Web Development

Backend Development

Building server-side applications with Django, Flask, and FastAPI

RESTful APIs

Creating scalable APIs for web and mobile applications

Web Scraping

Extracting data from websites using BeautifulSoup and Scrapy

Data Science & Analytics

Data Analysis

Analyzing datasets with Pandas, NumPy, and statistical methods

Machine Learning

Building predictive models with scikit-learn and TensorFlow

Data Visualization

Creating interactive charts and dashboards with Matplotlib and Plotly

Automation & Scripting

System Administration

Automating routine tasks and system management

Testing Automation

Creating automated test scripts for software quality assurance

DevOps

Building CI/CD pipelines and infrastructure automation

PySpark Use Cases

Big Data Processing

ETL Pipelines

Building extract, transform, load processes for large datasets

Data Warehousing

Processing and preparing data for analytical databases

Batch Processing

Handling large-scale batch data processing jobs

Real-time Analytics

Stream Processing

Analyzing real-time data streams from IoT devices or applications

Real-time Recommendations

Building recommendation engines that update in real-time

Fraud Detection

Identifying suspicious patterns in real-time transaction data

Machine Learning at Scale

Distributed Model Training

Training machine learning models on large datasets

Feature Engineering

Creating features from massive datasets for ML models

Model Serving

Deploying and serving ML models at scale

Python & PySpark Training Program | Total Estimated Duration: ~24 hours

All topics include free MCQ tests and interview questions to assess your understanding

Note: Durations are estimates and may vary based on individual learning pace