
Provide a topics overview emphasizing practical, hands-on Python programming, with setup for Python 3 on Windows and Raspberry Pi, Jupiter notebook access, and data processing using data frames.
Encourage students to provide honest feedback after exploring the full course, helping improve the training material and video courses. Emphasize thorough engagement before leaving ratings and reviews.
Learn to flash Raspberry Pi OS onto a Raspberry Pi 4 with the Raspberry Pi Imager and set up headless remote access over Wi-Fi, including IP discovery for remote connection.
Discover how to run Python 3 on Raspberry Pi, invoke the Python 3 interpreter, and work with pre-installed development tools to write and execute hello world programs.
Turn a Raspberry Pi 4 into a portable touchscreen tablet by assembling the SunFounder kit, wiring the display, microSD, power, Ethernet, USB, HDMI, cooling fan, and GPIO ribbon.
discover how to write and run a simple hello world program in Python 3 on Windows using the interpreter or the command prompt.
Compare Python 3 interpreter mode, an interactive memory-driven environment for prototyping, with script mode that runs saved files for data science and automation.
Learn to manage Python packages on Windows using pip: check version, upgrade, list, search, install, and uninstall libraries.
Install and verify Jupiter on a Raspberry Pi by installing the required kernel and dependencies, then launch the Jupiter notebook server and open it in the chromium browser.
Install putty on Windows by downloading the 64-bit installer from putty.org and running the setup with admin privileges. Add the executable to the path and verify by typing putty.
Launch a Jupyter notebook from a root directory, connect via an SSH tunnel, run Python in interactive cells, and save or rename notebooks with ipynb and other downloadable formats.
Explore NumPy, the core Python library for scientific computing, offering the ndarray data structure and operations to process multidimensional data for image, signal, and data science tasks.
Master numpy ndarrays by creating 1D, 2D, and 3D arrays, indexing elements, and slicing with colon syntax. Understand out-of-bounds errors and how to efficiently access data in Python.
Create and manipulate three by three matrices using ones, zeros, identity, and full functions, control diagonal position with k, and build n dimensional matrices for scientific computing.
Explore routines to create upper and lower triangular matrices in Python, with diagonals of ones and diagonal shifts controlled by k.
Explore matplotlib, an open-source Python plotting library with a MATLAB-like pyplot interface that enables 10–15 line plots, including bar charts, scatter plots, and 3D visuals in IPython or Jupyter notebooks.
Generate numerical ranges with arange and linspace and visualize data in Python. Plot x versus y, customize titles and axes, and explore linear, logarithmic, and geometric progressions.
Become a Master in Data Acquisition, Visualization, and Processing with Python 3 and acquire employers' one of the most requested skills of 21st Century! An expert level Data Science professional can earn minimum $100000 (that's five zeros after 1) in today's economy.
This is the most comprehensive, yet straight-forward course for the Data Science with Python 3 on Udemy! Whether you have never worked with Data Science before, already know basics of Python, or want to learn the advanced features of Pandas and plotly, this course is for you! In this course we will teach you Data Science and Time Series with Python 3, Jupyter, NumPy, Pandas, Matplotlib, and Plotly .
(Note, we also provide you PDFs and Jupyter Notebooks in case you need them)
With over 105 lectures and more than 12.5 hours of video this comprehensive course leaves no stone unturned in teaching you Data Science with Python 3, Pandas, and Time Series Analysis!
This course will teach you Data Science and Time Series in a very practical manner, with every lecture comes a programming video and a corresponding Jupyter notebook that has Python 3 code! Learn in whatever manner is the best for you!
We will start by helping you get Python3, NumPy, matplotlib, Jupyter, Pandas, and Plotly installed on your Windows computer and Raspberry Pi.
We cover a wide variety of topics, including:
Basics of Scientific Python Ecosystem
Basics of Pandas
Basics of NumPy and Matplotlib
Installation of Python 3 on Windows
Setting up Raspberry Pi
Tour of Python 3 environment on Raspberry Pi
Jupyter installation and basics
NumPy Ndarrays
Array Creation Routines
Basic Visualization with Matplotlib
Ndarray Manipulation
Random Array Generation
Bitwise Operations
Statistical Functions
Basics of Matplotlib
Installation of SciPy and Pandas
Linear Algebra with NumPy and SciPy
Data Acquisition with Python 3
MySQL and Python 3
Data Acquisition with Pandas
Dataframes and Series in Pandas
Visualization with Plotly
Advanced Matplotlib Visualizations
Data Processing
You will get lifetime access to over 105 lectures plus corresponding PDFs and the Jupyter notebooks for the lectures!
So what are you waiting for? Learn Data Science and Time Series with Python 3 in a way that will advance your career and increase your knowledge, all in a fun and practical way!