Welcome to CS205: Building with Artificial Intelligence

Specific information about this course and its requirements can be found below. For more general information about taking Saylor Academy courses, including information about Community and Academic Codes of Conduct, please read the Student Handbook.

Course Description

Get a broad, foundational introduction to the rapidly evolving field of artificial intelligence by learning how to build intelligent software solutions in today's business applications.

Course Introduction

After using a really smart app that produced amazing results within seconds, you must have asked yourself: 'How did it do that?' After you take this course, you will be able to start answering that question yourself! This course provides you with the fundamentals of the rapidly evolving field of artificial intelligence. Topics we will cover include: Intelligent Agents Various kinds of machine learning models Search algorithms (including heuristic and uninformed search) Iterative improvement algorithms Game playing, logic and automated reasoning Knowledge bases Natural language processing, including generative AI Reasoning under uncertainty You will need to know how to program in a modern language like Python, C#, or Java, and how to apply libraries that are readily available to apply the concepts you learn.

This course includes the following units:

Unit 1: What Is Artificial Intelligence?. Unit 2: Agent-Based Approach to AI. Unit 3: Machine Learning and Its Importance. Unit 4: Machine Learning Algorithms. Unit 5: Problem-Solving Methods in AI. Unit 6: Search Algorithms. Unit 7: Iterative Improvement Algorithms. Unit 8: Game-Playing Models. Unit 9: Natural Language Processing. Unit 10: Reasoning Agents

Course Learning Outcomes

Upon successful completion of this course, you will be able to:

[1] Analyze the definition of 'intelligence', from the Turing test to the four basic orientations of modern AI; [2] Analyze the concept of 'agents' in contemporary AI business solutions; [3] Analyze the different types of 'agents' and their capabilities; [4] Describe the different kinds of machine learning algorithms and their significance in building AI business solutions; [5] Apply supervised machine learning algorithms and contemporary libraries to build AI business solutions; [6] Explain the principles of unsupervised machine learning and reinforcement learning models; [7] Apply general AI-based problem-solving methods and their computational characteristics; [8] Apply heuristically based search algorithms to improve their optimality; [9] Apply natural language processing concepts and techniques with existing libraries for analysis and generative applications; [10] Discuss the principles of logical reasoning and reasoning under uncertainty; [11] Explain the basics of two-person, adversarial game-playing; [12] Throughout this course, you will also see learning outcomes in each unit to help organize your studies and gauge your progress

Throughout this course, you will also see learning outcomes in each unit. You can use those learning outcomes to help organize your studies and gauge your progress.

Course Materials

This course's primary learning materials are articles, lectures, and videos.

All course materials are free to access and can be found in each unit of the course. Pay close attention to the notes that accompany these course materials, as they will tell you what to focus on in each resource and will help you understand how the learning materials fit into the course as a whole. You can also see a list of all the learning materials in this course by clicking on Resources in the navigation bar.

Evaluation and Minimum Passing Score

Only the final examination is considered when awarding you a grade for this course. To pass this course, you will need to earn 70% or higher on the final exam. Your score on the exam will be calculated as soon as you complete it. If you do not pass the exam on your first try, you may take it again as many times as you want, with a 7-day waiting period between each attempt. Once you have successfully passed the final exam, you will be awarded a free Course Completion Certificate.

There are also end-of-unit assessments in this course. These are designed to help you study and do not factor into your final course grade. You can take these as many times as you want until you understand the concepts and material covered. You can see all of these assessments by clicking on Quizzes in the course's navigation bar.

Tips for Success

CS205: Building with Artificial Intelligence is a self-paced course, meaning you can decide when to start and complete the course. We estimate the "average" student will take 48 hours to complete. We recommend studying at a comfortable pace and scheduling your study time in advance.

Learning new material can be challenging, so here are a few study strategies to help you succeed:

  • Take notes on terms, practices, and theories. This helps you understand each concept in context and provides a refresher for later study.
  • Test yourself on what you remember and how well you understand the concepts. Reflecting on what you've learned improves long-term memory retention.

Technical Requirements

This course is delivered entirely online. You will need access to a computer or web-capable mobile device and consistent internet access to view or download resources and complete auto-graded assessments and the final exam.

To access the full course, including assessments and the final exam, log into your Saylor Academy account and enroll in the course. If you don’t have an account, you can create one for free here. Note that tracking progress and taking assessments require login.

For additional guidance, check out Saylor Academy's FAQ.

Optional Saylor Academy Mobile App

You can access all course features directly from your mobile browser, but if you have limited internet connectivity, the Saylor Academy mobile app provides an option to download course content for offline use. The app is available for iOS and Android devices.

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Fees

This course is entirely free to enroll in and access. All course materials, including textbooks, videos, webpages, and activities, are available at no charge. This course also contains a free final exam and course completion certificate.

Last modified: Saturday, 9 November 2024, 10:44 AM