AI Essentials Certification

🧠 Week 1: Introduction to AI & Foundational Concepts

Welcome to Week 1 of the AI Essentials Certification Program!

 

In this foundational week, we’ll set the stage for your journey into the world of Artificial Intelligence (AI). Whether you're completely new to the subject or brushing up on your knowledge, this week will give you the essential groundwork for understanding how AI works and why it matters.

Welcome to Week 1 of your AI Essentials Certification Journey.

Defining Artificial Intelligence (AI)

Artificial Intelligence (AI) is a branch of computer science and engineering that focuses on creating machines capable of performing tasks that typically require human intelligence.

Introduction to Machine Learning (ML)

Artificial Intelligence (AI) is the simulation of human intelligence in machines, enabling them to perform tasks such as learning, reasoning, problem-solving, and decision-making. 

Practice Your Week 1 AI Essentials Certification program definitions with interactive flash cards.

🧠 AI Essentials Week 1 Matching Quiz Instructions: Match each Term (Column A) with the correct Definition (Column B) by dragging and dropping each definition. Matching each definition with its term.

In this AI Essentials Week 1 Quiz, we will cover Lesson 1 and Lesson 2 of the AI Essentials Week 1 Learning Objectives. The Week 1 Quiz covers: Definition of AI: Learn what Artificial Intelligence means in everyday terms and why it’s more than just a futuristic idea. Real-World Examples: Discover how AI is integrated into devices and applications you use daily—like smartphones, voice assistants, and recommendation systems. Historical Evolution: Explore a brief timeline of AI, highlighting key milestones that have shaped its development and impact across various industries.

Week 2: Data, Algorithms, and the Learning Process in AI

Week 2 Agenda:

 

• Understand the role of data in AI and machine learning.

• Learn how algorithms operate and the types used in AI.

• Explore the process of training AI models.

• Examine the importance of model evaluation and bias mitigation.

• Hands-on experience training a simple AI model using Open WebUI.

Welcome to Week 2 of your AI Essentials Certification Journey.

Week 2: Lecture Lesson 1 – The Role of Data in AI

In artificial intelligence, data plays a foundational role. Without data, AI systems would have nothing to learn from and no context to operate within. Just as human intelligence is shaped by our experiences and observations, AI intelligence is built from patterns and insights extracted from data. Data serves as the raw material for training AI models, allowing them to recognize patterns, make predictions, and automate decision-making tasks.

Lecture Lesson 2 – Data Collection, Preprocessing, and Ethics in AI

Once we understand the importance of data in artificial intelligence, the next step is learning how data is collected and prepared for use in AI systems. Data collection is the process of gathering information that will later be used to train AI models. Depending on the project, data can be collected from a variety of sources—websites, sensors, cameras, surveys, social media, transactions, and more. In many cases, large public datasets are also available for researchers and developers to use. These datasets are often shared by universities, governments, and companies to support innovation and collaboration in the AI field.

Test your Week 2 knowledge with flashcards.

🧠 AI Essentials Week 2 Matching Quiz Instructions: Match each Term (Column A) with the correct Definition (Column B) by dragging and dropping each definition. Matching each definition with its term.

Week 2 Quiz A 40‑question multiple‑choice assessment covering Week 2’s core topics: the role of data in AI, data types (structured, unstructured, semi‑structured), data preprocessing techniques (cleaning, normalization, standardization), dataset concepts, and ethical considerations such as bias, privacy regulations (GDPR, CCPA), and explainability.

Week 3 Agenda – AI Essentials Certification Program

 

Week 3: Supervised, Unsupervised, and Reinforcement Learning

Welcome to Week 3 of your AI Essentials Certification Journey.

Lecture Lesson 1: Supervised and Unsupervised Learning

Artificial intelligence systems learn from data using different approaches, the two most common being supervised learning, a method where the model is trained on examples paired with correct answers or labels, and unsupervised learning, a method where the model discovers patterns in data without any labels provided.

Lecture 2: Reinforcement Learning Fundamentals

Reinforcement learning, a type of machine learning where an agent, an entity that makes decisions, interacts with an environment, the external system or scenario the agent operates in, to achieve a goal, learns by trial and error through rewards, positive signals for desirable actions, and penalties, negative signals for undesirable actions.

Test your knowledge of key terms talked about in Week 3 of this AI Essentials certification course.

🧠 AI Essentials Week 3 Matching Quiz Instructions: Match each Term (Column A) with the correct Definition (Column B) by dragging and dropping each definition. Matching each definition with it's term.

Week 3 Quiz – Short Description A 40‑question multiple‑choice assessment covering Week 3’s essential AI learning paradigms: supervised learning, unsupervised learning, reinforcement learning fundamentals, and advanced prompt engineering tactics.

Week 4: AI in Practice – Real‑World Applications and Ethical Considerations

Week 4 Agenda

 

• Understanding how AI is applied across different industries

• Exploring ethical considerations, biases, and responsible AI development

Welcome to Week 4 of your AI Essentials Certification Journey.

Lecture Lesson 1: Real‑World Applications of AI

 

Artificial intelligence is no longer confined to research labs; it powers critical systems across healthcare, finance, transportation, and education. In healthcare, AI‑driven medical diagnosis uses algorithms to analyze imaging data and detect diseases early—improving patient outcomes. 

Lecture Lesson 2: Ethical Considerations and Responsible AI (Expanded)

 

As AI systems grow more powerful and pervasive, ethical considerations must guide every stage of their development and deployment. Bias in AI, systematic errors that produce unfair outcomes, arises when training data reflects historical prejudices or imbalanced representation, causing models to favor certain groups over others.

Test your knowledge with this week's flash cards.

🧠 AI Essentials Week 4 Matching Quiz Instructions: Match each Term (Column A) with the correct Definition (Column B) by dragging and dropping each definition. Matching each definition with it's term.

Week 4 Quiz – Short Description A 40‑question multiple‑choice assessment covering Week 4’s topics on real‑world AI applications, industry use cases, and ethical considerations including bias mitigation, transparency, and regulatory frameworks.Week 4 Quiz – Short Description A 40‑question multiple‑choice assessment covering Week 4’s topics on real‑world AI applications, industry use cases, and ethical considerations including bias mitigation, transparency, and regulatory frameworks.

✅ AI Essentials Certification

Week 5 Agenda

Final Reflections, Mastery, and Certification Completion

Welcome to Week 5 of your AI Essentials Certification Journey.

Final Exam – Short Description A 100‑question multiple‑choice exam covering core AI concepts, prompt engineering tactics, learning paradigms, real‑world applications, and ethical considerations from Weeks 1–4.