Python courses

937 Courses

Machine Learning Basics

Sharpen your digital skills by leveraging predictive analytics across multiple industries with machine learning at the forefront. In collaboration with FutureLearn, join Sungkyunkwan University for a four-week course and stay ahead of the competition. Enhance your understanding of AI and machine learning's core ideas to become a tech-savvy playe.
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Microsoft AI & ML Engineering

Join the Microsoft AI & ML Engineering program, a detailed curriculum designed to equip you with essential skills and deep understanding in the flourishing fields of Artificial Intelligence and Machine Learning. Across five courses, this program covers foundational concepts to advanced topics, offering practical skills and hands-on experience i.
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Building Intelligent Troubleshooting Agents

Join our "Building Intelligent Troubleshooting Agents" course, where you'll explore the cutting-edge design and implementation of AI-driven solutions. This comprehensive course empowers you with the skills to create agents capable of diagnosing and resolving problems without human intervention. You will delve into topics like natural language.
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IBM AI Engineering

Coursera AI technology is anticipated to expand by 37.3% by the year 2030, according to Forbes. The IBM AI Engineering Professional Certificate, offered through Coursera, equips data scientists, machine learning engineers, software engineers, and technical specialists with skills to excel as AI engineers. Throughout the program, participa.
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Advanced AI and Machine Learning Techniques and Capstone

Join our Advanced AI and Machine Learning Techniques and Capstone course to explore high-level AI & ML strategies. This course culminates in a capstone project where you'll utilize comprehensive skills to tackle a real-world challenge. Throughout, you'll encounter state-of-the-art machine learning methods and delve into the ethical consider.
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Explainable AI in Python

Enhance your understanding of Explainable AI with this comprehensive course offered by DataCamp. Designed for data scientists and machine learning practitioners, you'll gain expertise in using Python's Scikit-learn, SHAP, and LIME to interpret and visualize AI model behaviors. Why is Explainable AI crucial? Transparent, accountable, and t.
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Machine Learning, Data Science and Generative AI with Python

Join our comprehensive, hands-on tutorial to delve into the realms of Machine Learning, Data Science, and Generative AI with Python. This course provides a deep dive into essential technologies and tools such as TensorFlow, GPT, OpenAI, and neural networks. Perfect for those seeking practical experience and aiming to advance their skills in m.
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Ensemble Machine Learning in Python: Random Forest, AdaBoost

Ensemble Machine Learning in Python: Random Forest, AdaBoost | Udemy Enhance your data science skills with our comprehensive course on ensemble machine learning in Python. Delve into powerful techniques like Random Forest and AdaBoost, as well as foundational ensemble methods such as Boosting, Bagging, and Bootstrap. This course is provided b.
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Data Science: Modern Deep Learning in Python

Immerse yourself in the world of data science with our course on Modern Deep Learning in Python. Designed for both beginners and experienced practitioners, this course offers a comprehensive exploration of cutting-edge deep learning methods using popular Python libraries like TensorFlow, Theano, Keras, PyTorch, CNTK, and MXNet. Leverage the.
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Python : Master Programming and Development with 15 Projects

Join our extensive Python course where you will delve into the complete Python programming landscape. This course offers a robust curriculum starting from the basics of Python and expanding into various fields such as Data Science, Data Visualization, Desktop Graphical Applications using Tkinter, and Machine Learning. With 15 hands-on project.
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Your speed of mastering the profession and success in this matter largely depends on which programming language you start learning first. How to choose it? Let's answer using a python ai course as an example.

What criteria should you use to choose your first language?

For learning to progress quickly, the programming language must have a simple syntax. It is desirable that it be high-level and flexible - then you can experiment with different options for solving the same problem.

Of course, it cannot be said that the choice of the first language always determines how successful the student’s future career path will be. But it can have a powerful impact on professional development as well as self-learning skills.

Even if we talk about spoken languages, you’ve probably heard the statement that the language a person speaks determines his thinking: “the number of languages you know, the number of times you are human.” This statement is also relevant for programming. Note that this skill is often described as an effective tool for developing thinking that teaches people to solve problems well.

When choosing the first language, the following criteria are also taken into account:

It’s difficult to name an ideal programming language to learn as a first language, but Python definitely meets most of the listed criteria, which means it can be safely recommended to beginners.

Scope of Python

Scripting languages are rapidly gaining popularity these days. They are already used to write software even more often than traditional system ones. Python is compatible with all major operating systems and platforms. You will learn this information at a python course. It is actively used in science, web development, Machine Learning, game creation, complex visual effects, and more.

Community, technical documentation

The Python language has gathered a large community of developers from all over the world who are engaged not only in its study, but also in its development. The documentation base related to Python is extensive and well-developed, so even a beginner will not have much difficulty finding answers to almost all questions that arise. He also has enough standard libraries for all occasions, and there are even more open-source repositories.

Simplicity

Because Python has a simple syntax, its code is easy to read and understand. Statements are terminated by the end of the line, and the block structure is determined by indentation.

Among the features of Python, it is worth highlighting the use of indentations that delimit blocks of code. Correct formatting is ensured by the interpreter, which prevents the creation of unreadable code. So if in other programming languages indentation is a “handwriting” and an art, then in Python it is one of the components of the syntax.

Python Strengths and Weaknesses

We have already noted above some of the advantages of a python certification course, now we propose to compare them with the disadvantages in order to objectively evaluate the language as the first one to learn.

Pluses

  1. Easy to learn.

  2. Laconic.

  3. Easy and understandable syntax.

  4. Interpretability.

  5. Wide scope of use.

  6. Demand.

  7. Dynamic typing.

  8. A large number of libraries.

  9. Lots of technical documentation and training materials.

  10. Cross-platform.

Minuses

  1. Slow program execution speed: Because dynamically typed languages execute code line by line, this makes it difficult to develop software that requires high performance. However, the programmer's productivity increases, which can be considered a kind of compensation.

  2. Programs written in Python require a lot of memory.

  3. Because there is no check during compilation, errors sometimes occur when executing the code. Because of this, very high-quality testing is required before production launch.

Conclusion

Python is a clear, easy-to-learn, universal, in-demand and promising language. Despite the presence of certain disadvantages, its advantages significantly outweigh all the disadvantages, especially when it comes to novice programmers. That's why a python online course from AI Eeducation is a great choice to start your IT career!