Python Job Oriented Training In Bhopal

Weeks 1-4: Python Basics & Foundations

• Week 1: Introduction to Python, Get Started, Syntax, Comments, and Variables
• Week 2: Data Types, Numbers, Casting, Strings, and Booleans
• Week 3: Operators, Lists, Tuples, Sets, and Dictionaries
• Week 4: Control Flow: If...Else, While Loops, For Loops

Weeks 5-8: Intermediate Python Concepts

• Week 5: Functions, Lambda Functions, Arrays
• Week 6: Classes and Objects, Inheritance, Iterators, Polymorphism
• Week 7: Python Scope, Modules, Dates, Math, and JSON
• Week 8: Regular Expressions, PIP, Try...Except, User Input, String Formatting

Weeks 9-12: File Handling & Data Science with Python

• Week 9: Python File Handling (Reading, Writing, Deleting Files)
• Week 10: Introduction to NumPy, Creating Arrays, Indexing, Slicing
• Week 11: NumPy Data Types, Copy vs View, Shape, Reshaping, Iterating
• Week 12: NumPy Array Operations: Join, Split, Search, Sort, Filter

Weeks 13-16: Advanced NumPy & Data Visualization

• Week 13: NumPy Random, Data Distributions, and Seaborn
• Week 14: NumPy ufuncs (Arithmetic, Logs, Summation, Trigonometric functions)
• Week 15: Introduction to Pandas, Series, DataFrames, Reading CSV/JSON
• Week 16: Analyzing Data in Pandas: Cleaning Data, Removing Duplicates, Correlations

Weeks 17-20: Data Science Concepts

• Week 17: Data Science Fundamentals, Data Preparation, DataFrames
• Week 18: Statistics: Percentiles, Standard Deviation, Variance, Correlation
• Week 19: Advanced Data Science: Linear Functions, Plotting, Slope, Intercept
• Week 20: Linear Regression, Regression Coefficients, P-Value, R-Squared

Weeks 21-24: Machine Learning Basics

• Week 21: Introduction to Machine Learning: Types, Terminology, Clustering
• Week 22: Regression Techniques: Linear Regression, Polynomial Regression
• Week 23: Classification Algorithms: Decision Trees, Logistic Regression
• Week 24: Model Evaluation: Confusion Matrix, ROC Curve, Cross Validation

Weeks 25-28: Deep Dive into Machine Learning

• Week 25: K-means Clustering, K-nearest Neighbors
• Week 26: Bootstrap Aggregation, Grid Search, Hyperparameters
• Week 27: Neural Networks & Deep Learning Introduction
• Week 28: TensorFlow Basics, Operations, Models, Training

Weeks 29-32: Final Projects & Advanced Concepts

• Week 29: Django: Project Setup, Models, Views, Templates
• Week 30: Django CRUD Operations, Admin Panel, User Authentication
• Week 31: Introduction to MySQL & MongoDB: Basic Queries
• Week 32: Capstone Project: Build a Complete Python Data Science or Web Application