Python for Busy People - Python Intro in 2 Hours

Install the Anaconda distribution to set up a Python environment, configure the path, and use Anaconda Navigator or Jupyter notebooks (or Google Colab) to run Python code.

Add the python quick course environment to Anaconda by importing the yaml file and activating the new environment, then launch and use Jupyter notebooks to run Python code.

Learn to run python notebooks on Google Colab by uploading to Google Drive, opening .ipynb files, executing code in the cloud, and installing libraries with !pip when needed.

Explore how to navigate and use Jupyter notebooks in the Python course environment and Google Colab, run code cells, switch between code and markdown, and manage kernels.

Explore how Python handles integers and floats by using it as a calculator, assign numbers to variables, perform operations, and check types with the type function.

Learn to import the math library in Python and call functions like sqrt, pi, log, ceil, and floor, using attributes and multiple arguments for practical calculations.

Explore Python strings, declare with quotes, concatenate, print, and master zero-based indexing, slicing, immutability, and basic type and len checks.

Explore Python lists: flexible, mutable containers created with square brackets that can hold mixed types, support zero-based indexing, element assignment, and basic printing demonstrations.

Explore how methods attach to objects in Python, showing string immutability with replace returning a new string, and list mutation with append that changes the original object in place.

Explore python sets and their ability to store distinct elements, using curly brackets and the list() conversion to show that sets are unordered and not indexable.

Explore Python dictionaries as a flexible key-value data structure, create them with curly braces, access values with keys in square brackets, and use items, keys, and values to inspect contents.

Explore the python tuple data structure, its immutability, and how indexing compares to lists, then learn when to use tuples to store objects efficiently.

Master python control flow by using if statements, elif and else branches with proper indentation. Explore how conditions direct code paths, compare equality, and prepare for for and while loops.

Explore Python loops by iterating through lists and tuples with for loops to greet each student, and learn to manage while loops to avoid infinite runs, using str for concatenation.

Define and call Python functions with def and return, pass arguments, and reuse code through simple and multi-argument examples, while mastering indentation and function calls.

Explore the numpy library for working with vectors, matrices, and tensors, create and index arrays, and understand shapes and multi-dimensional structures, setting the stage for pandas data frames.

Explore the pandas data frame, turning arrays into an Excel-like, sql tables, with columns and row indexes, using iloc and loc for indexing, and head and tail for views.

Open the Python quick course exercises, read the instructions, and implement code across practice sets using the math library for logarithms, then run validations against provided solutions.

Thank you for enrolling in the Python for busy people course. Discover a fast Python introduction and bonus links to the Python 16 hour course and natural language processing.