Online Course – Introduction to Artificial Intelligence: Certified Professional Internship at Google and the National Autonomous University of Mexico

Sixty years of artificial intelligence

Course 1 • 5 hours • 4.8 (416 ratings)

Course Details

What will you learn?

• In this course, offered by the National University of Mexico (UNAM), we will review the past, present, and future of artificial intelligence.
• We will also note the important concepts that will help in the continuation of the special program.
• We will discuss the social, ethical, and philosophical implications of developments in artificial intelligence.

Artificial inference

Course 2 • 20 hours • 4.1 (104 ratings)

Course Details

What will you learn?

• Formal inference plays an important role in artificial intelligence.
• There are two main ways to apply inference: one that emphasizes inference (logic), and the other that emphasizes uncertainty (probability theory).
• In this course, we will review an introduction to both logic (we will look at three types of logic) and probability theory (we will look at three probabilistic graphical models).
• Some of the tasks will require basic Python programming: the student must complete code that has been partially removed.

Troubleshooting through search

Course 3 • 18 hours • 4.6 (21 ratings)

Course Details

What will you learn?

• The course deals with the automatic solution of problems using search algorithms.
• You will learn how to abstract the problem as a graph of states-actions and measure its complexity by identifying parameters.
• We will also see how to analyze the consumption of computational resources of the algorithms to select or adapt the most suitable one for the problem.
• We would love to see you apply the algorithms to concrete problems.
• We will guide you through the implementation of algorithms in the Python programming language and show examples of their application to example problems.
• At the end, you will be able to test your algorithms in an interesting search space: solving a Rubik’s Cube.

Evolutionary computing

Course 4 • 19 hours • 4.1 (21 ratings)

Course Details

What will you learn?

• Evolutionary computing (EC) uses the theory of natural evolution and genetics for the evolutionary adaptation of computational structures.
• Provides an alternative means of dealing with complex problems in various fields, such as engineering, economics, chemistry, medicine, and the arts.
• The population of possible solutions to a given problem is likened to a population of living organisms that progress with each generation.
• By recombining the best individuals in the population and transferring the parents’ traits to their offspring.
• Various evolutionary methods have been developed in this field, which differ in the type of structures that make up the population.
• Evolutionary algorithms (AE) are defined as optimization and search methodologies that are influenced by and partially reflect the processes of natural evolution.
• Evolutionary algorithms are not the only optimization methods that originate from biological systems.
• There are a variety of optimization algorithms that attempt to mimic the behavior of natural systems.

Adaptive behavior

Course 5 • 9 hours • 4.5 (24 ratings)

Course Details

What will you learn?

• Life evolved in changing environments, and therefore developed mechanisms that allow them to exhibit adaptive behavior.
• Using synthetic methodology, we can build artificial adaptive systems that implement these mechanisms.
• We will build on examples from living systems, and examine various algorithms that allow systems to adapt themselves.
• We will also discuss issues related to resilience, which complements adaptation.
• Finally, we will see some applications of this type of artificial intelligence.
• In the final project, an artificial system will be developed that will exhibit adaptive behavior.

Computational creativity

Course 6 • 19 hours • 4.6 (11 ratings)

Course Details

What will you learn?

• What is creativity? Can computers be creative?
• How, when and why was this new field established?
• How far have we come in creating “creative” systems?
• What theories, methodologies, and developments can be used to program and evaluate this type of systems in narrative creation, music, scientific discovery, visual art, and more?
• We will analyze these questions and more, and discuss their implications throughout the course.
• As you progress through the lessons, you will gradually begin to build your creative adaptive agent.

Embodied cognition

Course 7 • 27 hours • 4.5 (37 ratings)

Course Details

What will you learn?

• Become familiar with the history and key terms in cognitive fields.
• Think about the importance of the body, environment, culture, and technology as well as dynamic processes in studying the brain.
• To examine open problems in cognition and artificial consciousness, as well as social aspects of cognition.

Artificial Intelligence: Final Project

Course 8 • 24 hours

Course Details

What will you learn?

• In the final project of the special program Introduction to Artificial Intelligence, students applied the terms acquired during the program to a problem of their choice.
• The project will include software development and article writing.
• It will address at least one of the topics discussed during the program, carrying out an implementation, comparing it with other techniques, and reporting the results in a paper.
• The goals of the project are:
• Apply the knowledge acquired during the specialized program in a specific field.
• To apply artificial intelligence technology for a specific purpose.
• Compare the created solution with existing solutions.
• Report the results in an organized article (up to 10 pages).