The Ultimate Python Course – Master Coding in Just 30 Days

Turn problems into algorithms, express them with pseudo code and flowcharts, and translate them into Python programs, with practical examples like minimum search and sorting.

Learn how to install Python via Anaconda on Windows, Linux, or Mac, launch Jupyter notebook from the Anaconda prompt, and prepare to write your first hello world program.

Launch and navigate the Jupyter notebook interface to write Python code and markdown, create code and markdown cells, run hello world, and export notebooks as pdf or slides.

Open the IPython shell and Jupyter notebook to run Python code, use it as a calculator, and learn how variables save and reuse results.

Explore how variables store data, dynamic typing, and common data types in Python, learn assignment, memory management, multiple assignment, and basic operators with examples in Jupyter Notebook.

Explore the bool data type, true and false values, and how to combine them with and, or, not, along with comparison operators to drive decision making in Python.

Explore built-in Python functions like round, diff mode (quotient and remainder), isinstance, pow, and input, with notes on tuples and simple type conversion.

Master Python control flow with if statements, elif and else, and nested ifs, while understanding indentation, comparisons, and boolean logic in Jupyter notebooks.

Master functions in Python: define with def, call and return values, and use docstrings and scope. Handle multiple and arbitrary arguments with *args and **kwargs for robust code.

Learn how to create and reuse Python modules, import them across files, manage module paths, and organize code into packages, with examples using NumPy, Pandas, and Matplotlib.

Explore strings in Python, declare with single or double quotes, concatenate with plus, and print. Learn indexing, slicing, immutability, and common string methods like strip, lower, replace, split.

Learn Python data structures—lists, tuples, sets, and dictionaries. Explore mutability, indexing and slicing, and how copying and nesting affect behavior, foundations for numpy and pandas.

Master numpy basics by creating and inspecting arrays, understanding dtype, ndim, and shape, and using array creation, indexing, slicing, reshaping, broadcasting, and random utilities.

Explore the pandas library by creating series and data frames, indexing with explicit and implicit indices, selecting data, handling missing values, and performing basic operations like grouping and masking.

Master matplotlib to create line plots, scatter plots, and 3D visuals using pyplot and numpy. Learn to generate data with linspace, plot with labels, colors, and multiple curves.

Explore covid-19 data with pandas and matplotlib to visualize deaths, confirmed, and recovered trends across 171 countries, and forecast future trends using scikit-learn, TensorFlow, or PyTorch.