The most used coding language on the planet today is Python. Python is at the top of the Pypl (Popularity of Programming Language) index, having seen a popularity boost of about 29% during 2018. Python ranked 8.53 percent, its highest ever ranking, on the Tiobe index of popular programming languages in June 2019, however it was still behind behind Java and C. In the next three to four years, Python is predicted to exceed its competitors Java and C at its present rate of advancement. Data scientists, web developers, and AI specialists all use Python. To be successful in the domains of data science and automation, you must have a solid understanding of Python.
The top 10 Python training courses, certifications, classes, tutorials, and classes for 2022 are listed here. Numerous users have profited from these resources, which include both free and paid courses appropriate for beginning, intermediate, and advanced learners.
There are no prerequisites for this beginner-level Python training course; anyone with fundamental programming knowledge can enrol. In fact, the first two courses are designed with complete beginners to programming in mind. The Python specialisation is divided into five classes, the last of which is a capstone project in which students create their own project to retrieve, analyse, and visualise data that they have or can find utilising the technologies they have learned in the programme.
Explain the fundamentals of computer programming using Python and create your own apps for data retrieval, processing, and visualisation Describe the fundamentals of structured query language (SQL) and database architecture for data storage
knowing basic programming principles like data structures
Use lists, dictionaries, and tuples, among other built-in data structures in Python, to carry out progressively complicated data analysis.
The overwhelming interest in this course is a sign of its high calibre. Starting with the fundamentals and working your way up to creating your own programmes and games, it teaches Python in an extremely professional manner. Older Python 2 notes are also included, although Python 3 is the main focus. This is a very thorough yet simple course to learn Python online, with over 100 lectures and 24 hours of on-demand video. The greatest approach to test and apply what has been learned is through the numerous quizzes, tests, programming assignments, and projects that are included.
Jose Portilla teaches this course in a very practical way. He first helps you get started by installing Python on your computer. After that, he walks you through live coding with each lecture and gives you access to the appropriate code notebook. For this course, no prior programming experience is necessary because it teaches Python completely from scratch.
Due to the advanced level of this specialisation, some familiarity with Python programming is required. It is also required that you have a basic understanding of statistics and maths. As listed below, each of the program's five classes teaches one or more free Python libraries:
- Introduction to Data Science covers NumPy, SciPy, and Pandas
2. In the course on Applied Plotting, Charting, Data Representation in Python, Matplotlib and Seaborn are covered.
3. Scikit-Learn is used in the Python course Applied Machine Learning.
4. NetworkX in the Python course on applied social network analysis. 5. NLTK and Gensim in the course on applied text mining
With the exception of the final two courses, which can be done concurrently, these courses are designed to be taken in the order listed and build upon one another. The certificate cannot be obtained without finishing all five courses. There are also a number of programming assignments to put the knowledge to the test and reinforce it.
The Learn Intermediate Python certification course imparts intermediate-level Python programming skills. It is perfect for people who wish to advance their skills but just have a basic understanding of Python and have built simple programmes using Python. The curriculum includes topics like Python objects, object-oriented programming, debugging, and control flow and equips students with the skills necessary for a range of positions in industries like data science, artificial intelligence, and software engineering.
