4 Best Online Python Data Processing Courses & Certification of 2023

It is extremely difficult for students with so many Python Data Processing courses to meet their needs. Learners often ask whether for each case there is a Python Data Processing course. The reply is YES. Popular courses are available below. Registration for the right course is a vital factor for your career advancement. This article selected the best Python Data Processing courses in 2023 by hand.

The main purpose is to illustrate each category of the best known and famous courses.

Based on your choice, choose one that best suits your needs.

However, let’s take a look at the best of the market’s Python Data Processing courses.

1. Data Processing with Python (Udemy)

Duration: 3-4 hours

Rating: 4.1 out of 5

This is an optimal course that teaches you how to use a programming language like Python to reduce processing time and to prepare them for your project. You will learn how Python can handle, clean and organize large quantities of data and access one million records of raw historic weather data. The course is designed by the professional Python programmer Ardit Sulce. It will help you learn how Python loads and extracts the data files, loads thousands of Python files using pandas, cleanse the data and much more.

Key Highlights:

  • Take a series of exercises that give you sample information to do the lessons you have learned so far.
  • Learn how to build Python pivot tables from large datasets, query data from CSV files from python pandas and KML Google Earth files.
  • Learn how statistics are calculated, the final data is visualized and Python used for data sets at each step.
  • Learn how to import data to Python for scanning and viewing from various sources such as delimited TXT files, CSV files, etc.

You can Sign up Here

2. Data Processing with Python by Nanjing University (Coursera)

Duration: 27 hours

Rating: 4.4 out of 5

This course is suitable for those candidates with no extensive programming experience because it will direct you to Python’s simple syntax. This course will teach you how to collect data locally and from the network in Python, how to provide data, and how to perform simple and advanced statistical analysis and data visualization. The entire course content is based on financial data so that students can more vividly feel Python’s simplicity, elegance, and strength. By the conclusion of the course, you will have a certificate of completion signed by the University, with tasks and projects.

Key Highlights:

  • Awareness of Python’s fast, convenient, and efficient data processing capability in the literature, sociology, and journalism industries.
  • A feasible curriculum with enhanced order of contents and information on extensive subjects to allow you to easily learn data processing.
  • Know how to develop a simple GUI for the presentation and processing of data.
  • Study with a 10 days free study course from the comfort of your home.
  • Get access to multiple video lectures with subtitles, quizzes, grading, exercises, and much more to develop your knowledge.

You can Sign up Here

3. Basic Data Processing and Visualization by UC San Diego (Coursera)

Duration: 14 hours

Rating: 4.4 out of 5

This course is part of the Python Data Products for Predictive Analytics program, which takes you through Python’s basics of reading and manipulating data sets. Enrolling in this course will help you learn what a data product is during several Python libraries to acquire, display, and process data. The course is developed by the specialist teachers in data processing and Python programming of the San Diego University of California. During the course, a team of experts will be available 24 hours a day to resolve any problems or questions related to course content.

Key Highlights:

  • Understand how data are handled in various formats, such as timestamps, strings, etc. and filter and clean outliers, etc.
  • Get a quick description of the area of data science and prepare for the next three specialization program courses.
  • Learn how the data strategy and process for data generation, collection, and consumption are developed.
  • Gain key skills during the course such as Python libraries, pre-processing data, web scraping, data visualization, etc.
  • Get the foundational technical training with libraries like NumPy and data intake with requests and urllib.

You can Sign up Here

4. Complete Data Science Training with Python (Udemy)

Duration: 12-13 hours

Rating: 4.3 out of 5

This tutorial is a comprehensive guide to Python Practical Data Science that lets you learn how to model statistics, visualize data, machine learning, and much more. It is a 12-hour Bootcamp course, designed with all the material necessary to develop your data analysis skills. All through your learning journey, users understand everything including simple visualization and data exploration to statistical analysis and machine learning and then learn how to apply simple deep learning models with Python. Minerva Singh, who has an MPhil degree from Oxford University, will help you on your entire journey of learning.

Key Highlights:

  • Have a full intro to Python Data Science and Python ‘s efficient data science platform, Anaconda.
  • Get a completion certificate signed by Udemy professionals that can be shared with employers to demonstrate your skills.
  • Learn how to preprocess and wrangle Python ‘s data through NAs / No data removal, conditional data handling, attribute grouping, etc.
  • Learn about simple analytical methods such as NumPy, Operations, Arrays, Parameters for Equations, Arithmetics, Vectors, Broadcasting, and more.
  • Learn at the end of the course how to create artificial neural networks and deep learning structures.

You can Sign up Here

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4 Best Online Python for Finance Courses & Tutorials of 2023

Wrapping Up

This is the list of the 4 Best Online Python Data Processing Courses & Certification of 2023. They are popular and loved by many data science learners. You will find between these courses what you need to learn in order to continue your data science learning path.

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