Python + AI
The Python course at iLearn24x7 provides a clear, step-by-step introduction to Python programming, covering core concepts, practical coding skills, and real-world applications. Designed for beginners, it builds a strong foundation and prepares learners to confidently use Python for automation, data analysis, and AI-driven tasks.
Who is this intended for, and what level of experience is required?
This course is intended for students, freshers, working professionals, and anyone interested in learning Python programming. No prior coding experience is required, as the course starts from the basics and gradually progresses to more advanced concepts, making it suitable for complete beginners as well as learners with some programming knowledge who want to strengthen their skills.
Prerequisites:
- Basic computer knowledge (No coding required)
Course Duration
6 Weeks
Week 1: Core Python & Data Handling
Week 1
- Introduction to Python & AI (conceptual overview)
- Python installation & setup
- VS Code
- Jupyter Notebook
- Python syntax & keywords
- Variables & data types
- Input/output operations
- Operators & expressions
- Conditional statements (
if,elif,else) - Loops (
for,while) - Practice problems & logic building
Week 2: Core Python & Data Handling
Week 2
- Strings & string methods
- Lists, tuples, sets
- Dictionaries
- Functions & modules
- Lambda functions
- File handling:
- TXT
- CSV
- Exception handling (
try,except) - Working with JSON
Week 3: Advanced Python & Data Analysis
Week 3
- Object-Oriented Programming (OOP)
- Classes & objects
- Inheritance
- Polymorphism
- Encapsulation
- Python libraries:
- NumPy (arrays, math operations)
- Pandas (DataFrames, data cleaning)
- Data visualization:
- Matplotlib
- Seaborn
- Mini Project:
- Data analysis & visualization dashboard
Week 4: Python Frameworks – Web & Backend Development
Week 4
- Introduction to Python frameworks
- Flask Framework
- Routing
- Templates
- Forms
- REST APIs
- Django Framework
- Project & app structure
- Models, views, templates
- Django ORM
- Admin panel
- Database integration:
- SQLite / MySQL
- Mini Project:
- Simple web application (CRUD)
Week 5: Automation, APIs & AI Integration
Week 5
- Python for automation
- File automation
- Email automation
- Web scraping (BeautifulSoup)
- Working with APIs
- REST APIs
- API requests using
requests
- Introduction to AI APIs (no ML coding)
- Using AI tools via APIs
- Text generation & analysis (API-based)
- Background tasks & scheduling
- Mini Project:
- API-based AI tool or automation script
Week 6: Advanced Frameworks, Deployment & Final Project
Week 6
- FastAPI Framework
- High-performance APIs
- API documentation (Swagger)
- Authentication & authorization basics
- Deployment basics:
- Hosting Python apps
- Environment setup
- Final Project (choose one):
- Web application using Django / Flask
- API-based AI chatbot (using AI APIs)
- Automation system
- Code optimization & best practices
- Resume building (Python roles)
- Interview preparation & common questions
Tools & Technologies Covered
- Python
- NumPy, Pandas
- Matplotlib, Seaborn
- Flask
- Django
- FastAPI
- REST APIs
- Jupyter Notebook
- VS Code
Begin your journey to mastering Python + AI with our comprehensive, industry-focused learning modules today.
Prerequisites:
- Basic computer knowledge (no coding required)
Course Duration
6 Months (24 Weeks)
Month 1: Python Programming Foundations
Week 1
- Introduction to Python & AI
- Python installation & IDEs (VS Code / Jupyter Notebook)
- Python syntax, variables, data types
- Basic input/output
Week 2
- Operators & expressions
- Conditional statements (
if,elif,else) - Loops (
for,while) - Practice problems
Week 3
- Strings & string methods
- Lists, tuples, sets
- Dictionary basics
Week 4
- Functions & modules
- Lambda functions
- Basic problem solving
Month 2: Advanced Python & Data Handling
Week 5
- File handling (CSV, TXT)
- Exception handling
- Working with JSON
Week 6
- Object-Oriented Programming (OOP)
- Classes & objects
- Inheritance
- Polymorphism
Week 7
- Python libraries for AI:
- NumPy (arrays, operations)
- Pandas (dataframes, analysis)
Week 8
- Data visualization:
- Matplotlib
- Seaborn
- Mini project: Data analysis
Month 3: Mathematics & Statistics for AI
Week 9
- Linear algebra basics
- Vectors & matrices
- Matrix operations
Week 10
- Probability basics
- Descriptive statistics
- Data distributions
Week 11
- Inferential statistics
- Correlation & covariance
- Hypothesis testing
Week 12
- Mini project: Statistical data analysis
Month 4: Machine Learning Fundamentals
Week 13
- Introduction to AI, ML & Deep Learning
- Types of ML:
- Supervised
- Unsupervised
- Reinforcement
Week 14
- Supervised learning:
- Linear Regression
- Logistic Regression
Week 15
- Classification algorithms:
- KNN
- Decision Trees
- Naive Bayes
Week 16
- Model evaluation:
- Train/test split
- Accuracy, precision, recall
- Confusion matrix
Month 5: Advanced Machine Learning & NLP
Week 17
- Unsupervised learning:
- K-Means clustering
- Hierarchical clustering
- Dimensionality reduction (PCA)
Week 18
- Ensemble techniques:
- Random Forest
- Gradient Boosting
Week 19
- Natural Language Processing (NLP):
- Text preprocessing
- Tokenization
- TF-IDF
Week 20
- NLP project:
- Sentiment analysis
- Chatbot basics
Month 6: Deep Learning & AI Projects
Week 21
- Neural networks fundamentals
- Perceptron
- Activation functions
Week 22
- Deep learning with TensorFlow / PyTorch
- Artificial Neural Networks (ANN)
Week 23
- Introduction to:
- Convolutional Neural Networks (CNN)
- Image classification
- Computer vision basics
Week 24
- Final AI Project:
- Face recognition / AI chatbot / Image classifier
- Model deployment basics
- Resume & interview preparation
Tools & Technologies Covered
- Python
- NumPy, Pandas
- Matplotlib, Seaborn
- Scikit-learn
- TensorFlow / PyTorch
- Jupyter Notebook
Begin your journey to mastering Python + AI with our comprehensive, industry-focused learning modules today.
About Trainer
With over 3 years of hands-on experience in Python and Django development, Rishant Sharma is a skilled and dedicated technology professional with a strong foundation in building robust, scalable web applications. Holding a Master of Computer Applications (MCA) degree, he combines solid academic knowledge with practical industry exposure to deliver effective, real-world solutions. His expertise spans backend development, problem-solving, and implementing best practices in modern software development.
