The Complete Scientific Python 3 Bootcamp

Install python 3 on windows using the official python.org installer, add to path, and verify installation; explore python's web development options (django, flask, web2py) and scientific computing use.

Verify that Python 3 is added to the system path and environment variables, locate python.exe and scripts, then run python -V or python --version and open IDLE to confirm.

Learn what a single board computer is, with Raspberry Pi as the example, its credit-card size, embedded components, non-upgradable design, and its role in low-cost embedded and IoT projects.

flash Raspberry Pi OS 64 bit onto a microSD card with the Raspberry Pi imager, enable headless wifi, and remotely access the Raspberry Pi via the remote desktop protocol.

Learn to access the Raspberry Pi desktop remotely using VNC by enabling the VNC server, installing the VNC viewer, and configuring resolution for a smooth graphical interface.

Install idle3, the integrated development and learning environment, on a Raspberry Pi running Raspbian. Update apt repositories, install idle3, and verify by launching the Python 3 prompt.

Explore Python 3 on Raspberry Pi, locate interpreters and IDLE, and write, save as a .py file, then build and run a hello world program with the built-in IDEs.

Learn to connect to a Raspberry Pi remotely using PuTTY, WinSCP, and MobaXterm, mastering remote file transfer, SSH login, and X11 forwarding for graphical apps.

Transform your Raspberry Pi 4 into a portable touchscreen tablet using the Sunfounder Raspad 3, following the assembly of display, power, cooling, and GPIO wiring.

Learn how to write and run a simple hello world program in Python 3 on Windows using the interpreter and the command prompt.

Discover how to write and run a Python hello world on a Raspberry Pi, using the Python 3 environment and the command line, set executable permissions, and use a shebang.

Compare interpreter mode and scripting mode in Python 3; explain invoking Python, prototyping in memory, saving and executing large scripts, and using automation for data science.

Start IDLE3 on Raspberry Pi and explore its shell and editor. Save Python files, run programs, and use editing tools like indentation, commenting, the class browser, and Python docs.

Compare Raspberry Pi 3 B Plus with MacBook Pro and a custom-built PC to reveal use-case trade-offs for small databases, python tasks, and data science.

Explore the Python package index and pip, understand the batteries included philosophy, and use the BHP utility to download and install third-party libraries—while contributing your own package.

Learn to use pip on Windows to manage Python packages, including upgrading pip, listing installed utilities, searching for packages in the Python Package Index, and installing or uninstalling libraries.

Master pip3 on the Raspberry Pi by upgrading pip, listing installed packages, searching the Python package index, and installing or uninstalling packages with sudo when necessary.

Install NumPy and Matplotlib on Windows by running pip install numpy and pip install matplotlib from an admin command prompt, then verify by importing NumPy and Matplotlib in Python.

Install numpy and matplotlib on a Raspberry Pi using pip3, upgrade numpy, install matplotlib, and verify by importing numpy and matplotlib in Python 3 for ready numerical and scientific programming.

Explore IPython and Jupyter, web-based notebooks for interactive computing, with markdown, rich text, and code execution across languages like Python, R, and Julia.

Install and run Jupyter notebook on Windows using an admin command prompt and pip install. Create a new Python 3 notebook, save it, and execute a hello world program.

Install and verify Jupyter on the Raspberry Pi by following commands to install and resolve dependencies, then launch the Jupyter notebook server and verify it opens in a browser.

Install PuTTY on Windows by downloading the 64-bit installer from putty.org, running the setup with admin privileges, and adding PuTTY to the environment path for easy access.

Connect to a remote Jupyter notebook running on a Raspberry Pi from Windows by launching a headless server, tunneling via SSH, and logging in with a token.

Explore starting a Jupiter notebook, remotely connecting to a Raspberry Pi, and writing Python 3 code in interactive cells, with saving, renaming, and markdown and kernel controls.

NumPy provides the ndarray data structure and fast operations for scientific computing in Python. Store multidimensional data, images, and signals, used by libraries in data science and machine learning.

Explore ndarrays in NumPy’s ecosystem, learn indexing and slicing for 1D, 2D, and 3D arrays, and master practical data access in Python.

examine ndarray properties by checking shape, number of dimensions, data type, size, bytes, and transpose in a three-dimensional array.

Explore numpy constants, including infinity, NaN, positive and negative zero, and print key mathematical and scientific constants such as e and gamma.

Learn to create and manipulate matrices of ones, zeros, and identity matrices, explore diagonals with k shifts, and build multidimensional arrays in numpy like syntax.

Explore routines to create upper and lower triangular matrices filled with ones, with the diagonal offset by k and visualize shifts such as -1, 0, or 1.

Matplotlib, a core scientific Python plotting library, offers Matlab-style visualization and 2D/3D plots, enabling bar charts and scatter plots in notebooks with minimal lines of code, free and open source.

Explore numerical ranges with linspace and arange, and visualize data using plotting techniques, titles, axis control, and log and geometric spaces in a Matlab-style visualization.

Learn to generate one- and multi-dimensional arrays of random integers with numpy, specifying size and bounds, including 3x3 matrices, for uses like random noise in signal processing.