Mentorship

Learning is a continuous process. Stanford University is offering some courses that may be your bridge to these careers. There is no fee or application needed.

1. Introduction to Computer Science 101

In CS101, participants play and experiment with short bits of "computer code" to bring to life to the power and limitations of computers. Everything works within the browser, so there is no extra software to download or install. CS101 also provides a general background on computers today: what is a computer, what is hardware, what is software, what is the internet. Anyone who has the ability to use a web browser may be successful in this course. No previous computer science experience is required.

🔗 https://lnkd.in/dhEJpvxG

2. Machine Learning Specialization

Break Into AI with Machine Learning Specialization. Master fundamental AI concepts and develop practical machine learning skills in the beginner-friendly, 3-course program by AI visionary Andrew Ng

🔗 https://lnkd.in/dGt8MvbR

3. Designing Your Career

This online course uses a design thinking approach to help people of any age and academic background develop a constructive and effective approach to designing their vocation. This course is primarily comprised of 5 career-oriented vocational wayfinding concepts, illustrated through videos and expanded through personal reflections and exercises.

🔗 https://lnkd.in/dyVaE78d

4. Introduction to Internet of Things

Advances in technology are making possible a more widespread adoption of IoT, from pill-shaped micro-cameras that can pinpoint thousands of images within the body, to smart sensors that can assess crop conditions on a farm, to the smart home devices that are becoming increasingly popular. But what are the building blocks of IoT? And what are the underlying technologies that drive the IoT revolution?

🔗 https://lnkd.in/dWt6KRTi

5. Databases: Advanced Topics in SQL

This course is one of five self-paced courses on the topic of Databases, originating as one of Stanford's three inaugural massive open online courses released in the fall of 2011. The original "Databases" courses are now all available on edx.org. This course is broad and practical, covering indexes, transactions, constraints, triggers, views, and authorization, all in the context of relational database systems and the SQL language. This course builds on concepts introduced in Databases: Relational Databases and SQL and is recommended for learners seeking to advance their understanding and use of relational databases.

🔗 https://lnkd.in/dFxkmBVy

6. Introduction to Game Theory

Popularized by movies such as "A Beautiful Mind," game theory is the mathematical modelling of strategic interaction among rational (and irrational) agents. Beyond what we call `games in common language, such as chess, poker, soccer, etc., it includes the modelling of conflict among nations, political campaigns, competition among firms, and trading behaviour in markets such as the NYSE. How could you begin to model keyword auctions, and peer to peer file-sharing networks, without accounting for the incentives of the people using them? The course will provide the basics: representing games and strategies, the extensive form (which computer scientists call game trees), Bayesian games (modelling things like auctions), repeated and stochastic games, and more. We'll include a variety of examples including classic games and a few applications.

🔗 https://lnkd.in/ddTmwEdZ

7. R Programming Fundamentals

This course covers the basics of R: a free programming language and software environment used for statistical computing and graphics. R is widely used by data analysts, statisticians, and data scientists around the world. This course covers an introduction to R, from installation to basic statistical functions. You will learn to work with variable and external data sets, write functions, and hear from one of the co-creators of the R language, Robert Gentleman.

🔗 https://lnkd.in/dTr_zm4w

8. Introduction to Cryptography

Cryptography is an indispensable tool for protecting information in computer systems. This course explains the inner workings of cryptographic primitives and how to correctly use them. Students will learn how to reason about the security of cryptographic constructions and how to apply this knowledge to real-world applications. The course begins with a detailed discussion of how two parties who have a shared secret key can communicate securely when a powerful adversary eavesdrops and tampers with traffic. We will examine many deployed protocols and analyse mistakes in existing systems. The second half of the course discusses public-key techniques that let two or more parties generate a shared secret key. We will cover the relevant number theory and discuss public-key encryption and basic key-exchange. Throughout the course students will be exposed to many exciting open problems in the field.

🔗 https://lnkd.in/dxttDDfh

9. Advanced Cybersecurity Program

In this short preview, you’ll get to glimpse our Advanced Cybersecurity Program. You’ll be introduced to concepts from two of our most popular cybersecurity courses, learning fundamental concepts in information security and practical applications in cybersecurity and executive strategy. With access to our learning portal, you’ll be able to watch notable video lectures, hear from a trusted industry leader, attempt a short exercise, and get a real feel for this program’s content.

🔗 https://lnkd.in/dwWT9xg9

10. Algorithms: Design and Analysis

In this course you will learn several fundamental principles of algorithm design. You'll learn the divide-and-conquer design paradigm, with applications to fast sorting, searching, and multiplication. You'll learn several blazingly fast primitives for computing on graphs, such as how to compute connectivity information and shortest paths. Finally, we'll study how allowing the computer to "flip coins" can lead to elegant and practical algorithms and data structures. Learn the answers to questions such as: How do data structures like heaps, hash tables, bloom filters, and balanced search trees actually work, anyway? How come Quicksort runs so fast? What can graph algorithms tell us about the structure of the Web and social networks? Did my 3rd-grade teacher explain only a suboptimal algorithm for multiplying two numbers?

🔗 https://lnkd.in/dsHV3HQM

11. CS50's Introduction to Programming with Python

An introduction to programming using a language called Python. Learn how to read and write code as well as how to test and "debug" it. Designed for students with or without prior programming experience who'd like to learn Python specifically. Learn about functions, arguments, and return values (oh my!); variables and types; conditionals and Boolean expressions; and loops. Learn how to handle exceptions, find and fix bugs, and write unit tests; use third-party libraries; validate and extract data with regular expressions; model real-world entities with classes, objects, methods, and properties; and read and write files.

🔗 https://lnkd.in/dRgRrW-q

12. Data Science: Capstone

By completing this capstone project, you will get an opportunity to apply the knowledge and skills in R data analysis that you have gained throughout the series. This final project will test your skills in data visualization, probability, inference and modelling, data wrangling, data organization, regression, and machine learning.

🔗 https://lnkd.in/dHEiewFk

13. Data Science: Machine Learning

You will learn about training data, and how to use a set of data to discover potentially predictive relationships. As you build the movie recommendation system, you will learn how to train algorithms using training data so you can predict the outcome for future datasets. You will also learn about overtraining and techniques to avoid it such as cross-validation. All of these skills are fundamental to machine learning.

🔗 https://lnkd.in/dennwWXq

14. Artificial Intelligence for Robotics

Learn how to program all the major systems of a robotic car. Topics include planning, search, localization, tracking, and control.

🔗 https://lnkd.in/ddNJsn7t

15. Game Theory 

The course will provide the basics: representing games and strategies, the extensive form (which computer scientists call game trees), Bayesian games (modelling things like auctions), repeated and stochastic games, and more. We'll include a variety of examples including classic games and a few applications.

🔗 https://lnkd.in/ddTmwEdZ