Course Information
Course Overview
Learn to master the Python programming language and how to use Python for advanced Data Handling
This video course will teach you to master Python 3, one of the most popular programming languages in the world.
You will learn to master Python's native building blocks and powerful object-oriented programming to make you able to use Python for Data Science and Machine Learning Data Handling tasks. You will learn to design your own advanced constructions of Python’s building blocks and execute detailed data handling tasks using these building blocks with limited assistance from file handling libraries.
You will learn:
Python Programming
Python's data types (integer, float, string)
Python’s native data structures (set, tuple, dictionary, list)
Python’s data transformers, functions, object orientation and logic
How to make your own custom advanced functions and how to generalize functions
How to make your own custom advanced objects
Data Handling
How to transform, manipulate, and calculate data
How to move data around between common file formats and data structures
How to use advanced multi-dimensional uneven data structures
Cloud Computing: To use the web browser-based Anaconda Cloud Notebook (Cloud-based Jupyter Notebook). Learn to use Cloud Computing resources in this course.
Option: To use the Anaconda Distribution (Windows, Mac, Linux, and more)
Option: Python environment fundamentals with the Conda package management system and command line installing/updating of libraries and packages – golden nuggets to improve your quality of work life.
And much more…
This course is an excellent way to learn to master Python and Data Handling! Data Handling is the process of making data useful and usable for data analysis. Most Data Scientists and Machine Learners spends about 80% of their working efforts and time on Data Handling tasks. Being good at Data Handling and Python are extremely useful and time-saving skills that functions as a force multiplier for productivity.
This course is designed for anyone who wants to
learn to Master Python 3 from scratch or the absolute beginner level
learn to Master Python 3 and knows another programming language
reach the Master - intermediate Python programmer level as required by many advanced Udemy courses in Python, Data Science, or Machine Learning
learn Data Handling with Python
learn advanced Data Handling and improve their capabilities and productivity
Requirements:
Everyday experience using a computer with Windows, MacOS, or Linux is recommended
Programming experience is not needed
The course only uses costless software
Walk-you-through installation and setup videos for Windows is included
This course is the course we ourselves would want to be able to enroll in if we could time-travel and become new students. In our opinion, this course is the best course to learn the Python and Data Handling.
Enroll now to receive 9+ hours of detailed video tutorials with manually edited English captions, and a certificate of completion after completing the course!
Course Content
- 2 section(s)
- 27 lecture(s)
- Section 1 Introduction
- Section 2 Master Python for Data Handling
What You’ll Learn
- Master Python Programming - data types, native data structures, data transformers, functions, and logic
- Data Handling - understand data handling, transform, manipulate, and calculate data. Move data between common file formats and data structures
- Advanced Data Handling - understand and use advanced multi-dimensional uneven data structures How to generalize functions
- Python Object Oriented Programming - understand object orientation, create custom advanced objects, methods, and and functions, learn to generalize functions
- Cloud Computing - use Anaconda Cloud Notebook (Jupyter Notebook). Learn to use Cloud Computing resources
- Optional: use Anaconda Distribution's Jupyter Notebook and Conda package management system
Skills covered in this course
Reviews
-
RRoss Ethridge
I appreciate the introduction to Anaconda cloud. I had never used it before.
-
AArjan Seijkens
The course was a bit slow for me, but I probably have too much programming experience already. Also I missed exercises, I would like more exercises, where also the solution to the exercise is handled. Next to that there was no real info on how to run the code outside of a Jupyter notebook, I would really like to have learned how to run Python code from command line on different environment (e.g. on my machine, vs. on someone else's machine or a computer part of a cluster). And I couldn't find the starting code for course "26. Python Object Oriented Programming IV: Recap and More" on course page
-
AAlexander Krause
Good python course with a practical view to data handling from many points of view.
-
JJavier Vaz
Great coding course. I was a bit rusty, but this course was easy to understand and relevant for moving data around. Thank you!