MITx Introduction to Computer Science and Programming Using Python
Being physically present in a classroom is no longer a single way to learn — not with the growth of the internet and new technology, at any rate. Nowadays, as soon as you can get online, you can achieve an excellent education anytime and wherever you choose. We are now beginning a new age – the online learning revolution.
You can learn or teach from anywhere in the globe with online education. This means that there is no need to commute or adhere to a rigid routine. Therefore, you not only save time, but also money, which can be spent on other priorities. The virtual classroom is also available everywhere there is an internet connection, and traveling is a great opportunity to take advantage of this. if you’re studying abroad and want to work, online education is a great option. There’s no need to stop working or studying when traveling to new and unusual locations.
Now I am going to talk about a course by which you can make money online:
Introduction to Computer Science and Programming Using Python
This course is about an introduction to computer science as a tool to solve real-world analytical problems using Python 3.5. This is the first of two courses: Introduction to Computer Science and Python Programming, and Introduction to Computational Thinking and Data Science. They are developed to allow people who have no previous experience with computer science or programming learn to think computationally and develop programs to solve relevant problems. Some students may utilize the two courses as a stepping stone to more advanced computer science courses, but for many, it will be their first and final computer science course. This run includes Python 3.5 course videos, lecture exercises, and problem sets.
#) It takes time Estimated 9 weeks
#) Take14–16 hours per week
#) This course is totally Free
#) Optional upgrade available
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You’ll Learn: –
1) You will know The Python programming language
2) Know about Some simple algorithms
3) You will be known about an informal introduction to algorithmic complexity and Data structures
4) The purpose is to provide students a quick overview of a variety of topics so that they will have an understanding of what is feasible when they need to think about how to utilize computation to achieve a goal later in their careers.
Instructor: John Guttag
He is the Dugald C. Jackson Professor of Computer Science and Electrical Engineering at MIT. He is the director of the Data Driven Medical Research Group at the Computer Science and Artificial Intelligence Laboratory. The group is working on applying sophisticated computational tools to medicine. Prediction of adverse medical events, prediction of patient-specific response to medicines, non-invasive monitoring and diagnostic tools, and telemedicine are all current initiatives. He has also conducted research, published papers, and given lectures in data networking, sports informatics, software defined radios, software engineering, and mechanical basic math.
Eric Grimson: -He is the Bernard M. Gordon Professor of Medical Engineering and a Professor of Computer Science and Engineering. From 2011 until 2014, he served as MIT’s Chancellor. Professor Grimson has been a member of the MIT faculty since 1984, formerly serving as chair of the Department of Electrical Engineering and Computer Science, assistant department head, and education officer. Professor Grimson is globally renowned for his computer vision research, particularly in applications in medical picture processing.
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Ana Bell: She is a lecturer in the Department of Computer Science and Electrical Engineering at MIT.
Professor Bell earned a Bachelor of Applied Science degree from the University of British Columbia in Vancouver, Canada. Princeton University awarded her an MA and a PhD. Her study was on computational biology.
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