10 Python Certifications You Should Get as a Beginner

10 Python certifications that help beginners who want to get more expertise as a Python developer

Any aspiring Python Developer should have some Python Certifications. These Python Certifications provide extensive knowledge of Python, one of the most popular programming languages. They provide students with the knowledge and abilities needed to thrive in Python programming. Here are 10 Python certifications that you should obtain as a beginning if you want to improve your résumé, credibility, and confidence with this programming language.

1. Python for Everybody Specialization from the University of Michigan (Coursera):

The Python specialization is a beginner-level training program that requires no prior programming knowledge and covers the following topics:

• Python programming essentials
• Structured Query Language (SQL) and database design for data storage
• Data structures and other key programming concepts
• Using Python's built-in data structures like lists, dictionaries, and tuples for complicated data processing.

2. Complete Python Bootcamp: Go from zero to hero in Python 3 (Udemy):

This tutorial is a full and practical introduction to Python 3, with some comments on Python 2. Quizzes, examinations, and projects are also included in the course to help students assess and apply what they've learned. The course covers the following Python essentials:

• The collections module and how to interact with timestamps
• Object Oriented Programming using Classes
• The Jupyter Notebook system and how to create.py files
• Three big projects to develop a Python portfolio
• Python game creation, including Tic Tac Toe and Blackjack

3. Applied Data Science with Python Specialization from the University of Michigan (Coursera):

The specialization consists of the following five courses, each concentrating on one or more free Python libraries:

• Data Science Fundamentals: NumPy, SciPy, and Pandas
• Python Plotting, Charting, and Data Representation: Matplotlib and Seaborn
• Scikit-Learn: Applied Machine Learning in Python
• Text Mining in Python Using NLTK and Gensim
• NetworkX: Applied Social Network Analysis in Python

4. Python for Data Science and Machine Learning Bootcamp (Udemy):

The following Python for data science topics are covered in the course:

• Python fundamentals and libraries, such as NumPy, Pandas, Seaborn, Matplotlib, Plotly, and others.
• Data analysis and visualization: descriptive statistics, exploratory data analysis, interactive graphs, and so on.
• Machine learning techniques and algorithms: linear regression, logistic regression, k-means clustering, random forest, decision trees, and so on.
• Natural language processing and spam filters: text processing, sentiment analysis, spam detection, and so on.
• Neural networks and deep learning: TensorFlow, Keras, convolutional neural networks, recurrent neural networks, and so on.
• Big data analysis with Spark: Spark installation, Spark data frames, Spark SQL, and so on.

5. Learn Python Nanodegree Programs (Udacity):

This course offers practical skills with Python that are relevant to various fields, They are designed and taught by industry experts who work in the field, They involve real-world projects that are built in partnership with top-tier companies, They help learners build a portfolio of projects that showcase their Python skills, They offer flexible learning programs that allow learners to learn at their own pace.

6. Python Programming Masterclass (Udemy):

The course provides a thorough and engaging introduction to Python programming. The course covers the following Python fundamentals:

• Learn Python from skilled software engineers with years of experience.
• Be familiar with both Python 2 and Python 3.
• Learn how to write your own Python programs.
• Include Python Object-Oriented Programming (OOP) abilities in your resume.
• Up-to-date course content and full instructor assistance

7. Professional Certificate in Introduction to Computing in Python by Georgia Tech (edX):

Python certification curriculum that covers three areas of computer science and programming. The program covers the following Python fundamentals:

• Understand the core design cycle of computer science and programming: developing code, running it, analyzing the results, and modifying the code in response to the results.
• Acquire knowledge of procedural programming, control mechanisms, and data structures.
• In Python, learn about recursion, search and sort algorithms, and object-oriented programming.

8. Python for Data Science by IBM (Coursera):

This course goes into great detail on the following topics:

• Python fundamentals such as syntax, variables, operators, expressions, and so on.
• Python data structures: strings, lists, dictionaries, and file manipulation
• Python programming fundamentals: conditionals, loops, functions, and error handling
• Working with data in Python: pandas, numpy, and other libraries
• Project to analyze US economic data and create a dashboard

9. The Python Bible | Everything You Need to Program in Python (Udemy):

This course is appropriate for anyone who wishes to study Python for web development, data research, or robotics (Raspberry Pi). The course covers the following Python essentials:

• Learn Python 3 and create 11 Python projects
• Use variables to track data in Python programs
• Use numbers to create "behind-the-scenes" functionality
• Use strings to create customized, engaged user experiences
• Create programs that can think using logic and data structures
• Use loops to improve efficiency, save time, and maximize productivity

10. Learning Python (LinkedIn Learning – Lynda):

The course in question covers the following Python fundamentals:

• Learn the fundamentals of Python programming.
• Study dates and times, read and write files, and retrieve and interpret HTML, JSON, and XML data from the web.
• The View Offline option allows students to see course videos and content on their mobile devices without connecting to the internet.
• Regular evaluations and case studies