Online courses directory (121)
Computer programming skills are now becoming part of basic education as these skills are increasingly of vital importance for future job and career prospects. This free online course introduces you to the core components of programming using the Python programming language which is one of the most popular programming languages worldwide. The course shows you how to use the free open-source PyScripter IDE for Python to write basic programs using concepts such as functions, variables, If Else statements, For loops, While loops, iterative and recursive programs and algorithms such as the Insertion Sort algorithm. This course will be of great interest to all learners who would like to gain a thorough knowledge and understanding of the basic components of computer programming using the Python language – and might be a gentle introduction to programming for those who think they might have a longer term interest in the subject area. <br />
This course is part of the Microsoft Professional Program Certificate in Data Science.
Python is a very powerful programming language used for many different applications. Over time, the huge community around this open source language has created quite a few tools to efficiently work with Python. In recent years, a number of tools have been built specifically for data science. As a result, analyzing data with Python has never been easier.
In this practical course, you will start from the very beginning, with basic arithmetic and variables, and learn how to handle data structures, such as Python lists, Numpy arrays, and Pandas DataFrames. Along the way, you’ll learn about Python functions and control flow. Plus, you’ll look at the world of data visualizations with Python and create your own stunning visualizations based on real data.
Brand new to text-based programming? Check out this hands-on course for an in-depth look at the details of Python layers and concepts. Get ample practice drills and projects, using Jupyter Notebooks on Azure, which require only a browser and an Internet connection. Learn best practices and begin coding almost immediately.
After you explore data types and variables, take a look at strings, input, testing, and formatting. From there, learn about arguments and parameters, along with conditionals and nested conditionals. By the end of the course, you’ll be able to create programs that prompt users for input and use conditional (True/False) logic and Python methods to manipulate numbers and text to provide responses to the users, in addition to requesting further input. Plus, learn basic troubleshooting for your code. Sign up, and get started coding right away!
Ready for next steps? Take the python-fundamentals-microsoft-dev274x">Introduction to Python: Fundamentals course.
Ready for more hands-on, step-by-step Python fundamentals? Add to the foundational experience you got in the python-absolute-beginner-microsoft-dev236x">Introduction to Python: Absolute Beginner, and explore data structures. Get lots of practice working with sample code in Jupyter Notebooks on Azure, which require only a browser and an Internet connection.
Focus on Python data structures, and work with string, list, and range sequences. Discover the power of list iteration, and learn about string and list methods. From there, get the details on file input and output—open files, read them, add to them, close them, and more. At the end of the course, you’ll be able to slice strings into substrings, create lists, iterate through them, import files, and use file append mode, along with a lot of other practical Python tasks, as you get started coding.
Interested in learning a computer programming language but unsure of how and where to begin? This course, Learn to Program Using Python, is a great place to start.
Python is an easy and fun language to learn, and it is now one of the most popular programming languages, suitable for almost any task from developing graphical user interfaces to building web applications.
This course is an introduction to the Python programming language. This course is open to all learners who wish to gain an understanding of the basic components of computer programming. You will learn basic computer programming concepts and terminologies such as variables, constants, operators, expressions, conditional statements, loops, and functions. This Python course includes hands-on exercises to help you understand the components of Python programming while incrementally developing more significant programs. The exercises in this course will be based on small assignments which will relate to real-world problems.
No previous programming knowledge needed.
Do you want to build systems that learn from experience? Or exploit data to create simple predictive models of the world?
In this course, part of the Data Science MicroMasters program, you will learn a variety of supervised and unsupervised learning algorithms, and the theory behind those algorithms.
Using real-world case studies, you will learn how to classify images, identify salient topics in a corpus of documents, partition people according to personality profiles, and automatically capture the semantic structure of words and use it to categorize documents.
Armed with the knowledge from this course, you will be able to analyze many different types of data and to build descriptive and predictive models.
All programming examples and assignments will be in Python, using Jupyter notebooks.
How do populations grow? How do viruses spread? What is the trajectory of a glider?
Many real-life problems can be described and solved by mathematical models. In this course, you will form a team with another student and work in a project to solve a real-life problem.
You will learn to analyze your chosen problem, formulate it as a mathematical model (containing ordinary differential equations), solve the equations in the model, and validate your results. You will learn how to implement Euler’s method in a Python program.
If needed, you can refine or improve your model, based on your first results. Finally, you will learn how to report your findings in a scientific way.
This course is mainly aimed at Bachelor students from Mathematics, Engineering and Science disciplines. However it will suit anyone who would like to learn how mathematical modeling can solve real-world problems.
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