Learn about an area of interest with a variety of courses offered by the Massachusetts Institute of Technology, better known as MIT.
Below, we leave you the courses, brief descriptions and direct links to each of them, so that you can to use you just have to give Click on course nameIn this way you will be redirected to the platform where you will take the said course.
First of all, let us tell you that these courses can be found on the famous edX platform and they are:
with online mode
totally free
Easily learn at your own pace (you choose the time of day to learn)
With the option of official certification (this document has a cost, it is established by the same portal)
10 free and virtual courses offered by MIT
supply chain analysis
Its objective is for you to know and learn about the most basic analytical models, how to apply them, as well as the construction and solution of statistical and optimization models in supply chains.
The course lasts 15 weeks, consisting of 8 to 12 hours each week, and your instructor will be Chris Caplice, Director of the MITX MicroMasters in Supply Chain Management program.
Machine Learning with Python
During the course you will learn and understand the principles behind machine learning problems (classification, regression, clustering and reinforcement learning). You will also learn how to apply and analyze linear models, graphical models, etc.
In turn, you will also learn how to implement and organize machine learning projects (training, validation, parameter tuning, and feature engineering).
It lasts 15 weeks, taking 10 to 14 hours for each of these weeks, and will require you to have knowledge in Python programming, equivalent probability, calculus, and vectors and matrices.
Your instructors will be Regina Barzilay, Tommy Jaakkola, and Karen Chu, all professors at MIT.
Understanding the world through data
At the end of the course you will be able to know Python programming, as well as gain knowledge of dependent and independent variables, generate relationships between data and identify them using linear and polynomial regression models.
You will take 4 modules, divided into 9 weeks of course, and taught by MIT natives Alexander Madry, Anna Bell, Silvina Hanono Wachman.
become an entrepreneur
Throughout the course you will learn how to define an entrepreneur’s objectives, identify business opportunities, study markets and how to choose customers, as well as design and test offers and plan the logistics of the business.
All the above will give you skills for commerce, and thus you will be able to make the most of it for your entrepreneurship.
It lasts 6 weeks, 1 – 3 hours each week, and your instructors will be Martin Culpepper and Laurie Stach from MIT.
Fundamentals of Modern Finance
This course lasts for 12 weeks, and you will be required to complete 10 to 14 hours for each of these weeks. This may seem like a lot, but the truth is that if you learn how to distribute yourself it won’t even take 3 hours of your day. Schedule well.
You are expected to learn about risk analysis, pricing principles and the introduction to corporate finance, as well as gain knowledge about derivative securities, portfolio theory and corporate financial decisions.
You will have Leonid Kogan, Hiang Wang and Igor Marveyev from MIT as instructors.
Introduction to Biology-Mystery of Life
The purpose of the course is for you to learn to describe the most basic components of life, the functions of biology, to predict the genotype and phenotype (based on genetic data), as well as to know the central dogmas of molecular biology, in order to apply To be. Principles of modern biology and converting DNA sequences into RNA.
To understand this course, it is necessary that you have prior knowledge of Biology and Chemistry.
Introduction to Computing and Programming Using Python
The purpose of this course is for you to learn about computing, the Python programming language, simple algorithms, as well as an introduction to algorithm complexity and data structures.
You’ll have access to videoconferences, exercises, and more, and you don’t need any experience to enter the course other than the most basic knowledge of algebra and mathematics.
The course lasts 9 weeks, and your instructors will be Professors John Guttag, Eric Grimson, and Anna Bell from MIT.
Introduction to Computational Thinking and Data Science
You will gain knowledge of stochastic programming and statistical thinking, as well as how to create diagrams with the pylab package.
You will write programs that simulate a robber cleaning a room in addition to other activities that will provide you with the necessary knowledge and understanding of computational complexity.
The courses last for 9 weeks, each of which takes 14 to 16 hours, and your instructor will be; John Guttag, Eric Grimson and Anna Bell.
Computational thinking for modeling and simulation
With a duration of 9 weeks and 3 to 5 hours of meetings for each of these, this course will teach you the selection and implementation of interpolation methods as well as simple methods for numerical integration and programs for solving equations (linear and Provides comprehensive knowledge in writing. non-linear).
Your instructors will be Daniel Frey and Ali Talabinejad from MIT.
Probability: The Science of Uncertainty and Data
The aim of the course is for you to acquire knowledge of probability models, random variables, probabilistic calculations, estimation methods, as well as the basic structure and elements of random processes.
You will also learn the most basic concepts of probability, its main tools and laws. You’ll learn all this under the tutelage of MIT’s Noah Tsitsiklis and Patrick Jallette over a 16-week period, which is how long the course lasts.
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