Course Brief
Learn Python, a versatile programming language used in web development, data science, and automation. This course covers fundamentals like syntax, variables, and control flow, as well as object-oriented programming. You'll also explore Python libraries for tasks such as file handling, data manipulation, and creating graphical user interfaces.
- Course overview
- Setting up your programming environment
- Basic syntax and data types (numbers, strings, booleans)
- Variables and operators
- Input and output (print, input)
- Conditional statements (if/else, elif)
- Loops (for, while)
- Logical operators (and, or, not)
- Flow control structures (break, continue)
- Handling errors and exceptions
- Defining and calling functions
- Passing arguments and return values
- Lambda expressions
- Scope and namespaces
- Using modules and packages (import)
- Lists (mutable, ordered, can contain duplicates)
- Tuples (immutable, ordered, cannot contain duplicates)
- Dictionaries (key-value pairs, mutable)
- Sets (unique elements, unordered, mutable)
- Comprehensions (list, dictionary, set comprehensions)
- Advanced operations and manipulations (slicing, indexing, sorting)
- Iteration and data structure algorithms (for loops, list comprehensions)
- Object-oriented concepts (classes, objects, attributes, methods)
- Defining classes and objects
- Inheritance (creating subclasses from parent classes)
- Polymorphism (dynamic method resolution)
- Data encapsulation and attributes (public, private, protected)
- Built-in methods and operators overloading
- File handling and working with external data (reading, writing, CSV, JSON)
- Regular expressions for string manipulation (matching, searching, extracting)
- Networking and web scraping (requests library)
- Graphical user interfaces (GUI) development (PyQt, Tkinter) (optional)
- Connecting to databases and data analysis (pandas, SQLAlchemy) (optional)
- Flask or Django framework for web development
- Building basic web applications (routing, templates, forms)
- Handling user input and data (GET, POST requests, sessions)
- Deploying web applications (Heroku, PythonAnywhere)
- Introduction to data science (data collection, cleaning, preparation)
- NumPy and pandas libraries for data manipulation (arrays, dataframes)
- Machine learning concepts and algorithms (supervised, unsupervised learning)
- Introduction to artificial intelligence (neural networks, deep learning)
- Error handling and debugging techniques
- Testing and test-driven development (unittest, pytest)
- Object-oriented design patterns (MVC, singleton, factory)
- Working with external APIs (RESTful APIs, web services)
- Performance optimization and memory management
- Data visualization and storytelling using Matplotlib, Seaborn
- Data mining and feature engineering
- Machine learning model evaluation and selection
- Introduction to deep learning frameworks (TensorFlow, PyTorch)
- Introduction to DevOps and automation concepts
- Working with the command line (shell scripting)
- Configuration management tools (Ansible, Puppet)
- Continuous integration and continuous delivery (CI/CD)
- Cloud computing and infrastructure automation (AWS, Azure)
- Building a portfolio of Python projects
- Job hunting and resume preparation for Python developers
- Freelancing and consulting opportunities
- Staying up-to-date with Python trends and technologies
- Networking and building a community of Python developers
"I will be the leader of a company that ends up being worth billions of dollars, because I got the answers. I understand culture. I am the nucleus. I think that’s a responsibility that I have, to push possibilities, to show people, this is the level that things could be at."
