Instructing machines to have intelligence similar to humans' intelligence and teaching them how to act and think as humans have long been a human dream. Artificial intelligence (AI) is a field of study that comes to corporate with new human lifestyles to fulfill human's desire to build machines that can think rationally. AI is accomplished by studying the patterns of the human brain and by analyzing the cognitive process. The outcome of these studies develops intelligent software and systems. AI has numerous applications in today's world; from self-driving cars to a simple chatbot or even a YouTube video recommender, or the Google translate, it can be seen everywhere. AI has transformed today's businesses and industries' attitudes toward some tasks that humans usually had done.
TechClass Fundamentals of Artificial Intelligence online course is a gentle introduction to AI's basic concepts and methodologies from theoretical and practical perspectives. The course covers essential intuitions behind different AI methods (e.g., machine learning and deep learning) as well as the business-side topics, like the implications of AI and its effect on today's industry. By the end of this course, you will be familiar with modern AI aspects as your very first steps on the journey to AI. You will learn to think outside the box using AI and present AI-based solutions using appropriate methods discussed in the course.
Learning outcomes
- Learn the fundamental definitions and concepts of AI, Machine Learning, and Deep Learning
- Get familiar with the history of AI and its primitive applications
- Understand the concept of data for modern AI
- Learn the difference between classical AI and modern AI (e.g., Machine Learning)
- Get familiar with the different types of Machine Learning algorithms and Neural Networks
- Get familiar with the related fields to AI, such as Computer Vision, Speech Processing, and NLP
- Understand the influential role of AI in today's industry and get familiar with some industrial applications of AI and Machine Learning
- Learn the pipeline/workflow of a Machine Learning project
- The student knows the different job positions related to Data Analysis, AI, and Machine Learning
- Get familiar with the methods to incorporate AI in a business and the requirements of an AI team
- Get familiar with some problems of AI, including the concept of bias, the impact of AI on jobs and public privacy, and the adversarial attacks on AI
Table of contents
Chapter 1: Intro to Course
- 1.1. Welcome!
- 1.2. About TechClass Data Science Department
- 1.3. Learning Outcomes
- 1.4. Your Expectations, Goals, and Knowledge
- 1.5. Abbreviations
- 1.6. Copyright Notice
Chapter 2: Introduction
- 2.1. What is AI?
- 2.2. Intelligent Agents
- 2.3. Thinking Humanly
- 2.4. Acting Humanly
- 2.5. Thinking and Acting Rationally
- 2.6. Chinese Room Argument
- 2.7. Strong AI vs. Weak AI
- 2.8. History of AI
Chapter 3: Modern AI
- 3.1. What is Data?
- 3.2. Classical AI vs. Machine Learning
- 3.3. Machine Learning vs. Deep Learning
- 3.4. Some Applications of AI
Chapter 4: Machine Learning
- 4.1. General Concepts
- 4.2. Supervised Learning
- 4.3. Unsupervised Learning
- 4.4. Reinforcement Learning
- 4.5. Neural Networks
- 4.6. Deep Learning
- 4.7. Crucial Hints for Model Training
- 4.8. Machine Learning and Related Fields
Chapter 5: AI and Machine Learning in Industry
- 5.1. AI as an Indispensable Part of Today’s Industry
- 5.2. Some Machine Learning Use Cases in Industry
- 5.3. Pipeline of a Machine Learning Project
- 5.4. A Closer Look at an AI-based Product
- 5.5. Different Roles in an AI Team
- 5.6. Strategies to Incorporate AI in Your Company
- 5.7. AI Team Requirements in Your Company
Chapter 6: Problems of AI
- 6.1. Bias in AI
- 6.2. AI and Privacy
- 6.3. Adversarial Attacks on AI
- 6.4. Impact of AI on Jobs
Chapter 7: Our Future with AI
- 7.1. What Can be Expected from the Future of AI?
- 7.2. Will Machines Obtain Consciousness?
- 7.3. Advice for a Better Future with AI
Chapter 8: Final Tasks
- 8.1. Project
- 8.2. Self-study Essay
Chapter 9: Finishing the Course
- 9.1. What We Have Learned
- 9.2. Where to Go Next?
- 9.3. Your Opinion Matters
- 9.4. Congrats! You did it!
Brochure
