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AI Explorer: From Basics to Brilliance

Embark on a transformative journey into the world of Artificial Intelligence with "AI Explorer: From Basics to Brilliance." This comprehensive course is designed for learners of all backgrounds—no prior AI expe…

★ 0.0 (0 reviews) 👥 1 students 📚 40 lessons ⏱ 6.9h
UI
Instructor
Utibe Inyang
📚
₦20,000
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📚40 lessons
♾Lifetime access
🏆Certificate included

What you'll learn

✓Understand the fundamental concepts and history of Artificial Intelligence.
✓Master Machine Learning, Deep Learning, and Neural Network architectures.
✓Apply Natural Language Processing (NLP) and Computer Vision techniques.
✓Build and deploy ethical AI solutions using real-world tools and frameworks.
✓Create a portfolio-ready capstone AI project from scratch.
✓Navigate AI career paths and ethical considerations confidently.

Course Curriculum

Section 1: Foundations of Artificial Intelligence
10 lessons
📝 1.1 – What is AI? A Simple Introduction 🔒 10:00
📝 1.2 – A Brief History of AI 🔒 12:00
📝 1.3 – Types of AI: Narrow, General, and Super 🔒 11:00
📝 1.4 – Core Concepts: Data, Algorithms, and Models 🔒 12:00
📝 1.5 – The AI Project Lifecycle 🔒 13:00
📝 1.6 – Quiz: Foundations Checkpoint 🔒
📝 1.7 – Hands-On: Exploring AI Tools 🔒
📝 1.8 – Ethical Foundations of AI 🔒 14:00
📝 1.9 – AI in the Real World: Industry Applications 🔒 15:00
📝 1.10 – Section 1 Wrap-Up & Capstone Prep 🔒
Section 2: Machine Learning & Deep Learning
10 lessons
📝 2.1 – Introduction to Machine Learning 🔒 12:00
📝 2.2 – Supervised Learning: Regression & Classification 🔒 14:00
📝 2.3 – Unsupervised Learning: Clustering & Association 🔒 13:00
📝 2.4 – Reinforcement Learning: Learning from Rewards 🔒 14:00
📝 2.5 – Neural Networks Demystified 🔒 15:00
📝 2.6 – How Neural Networks Learn: Backpropagation & Gradient Descent 🔒 16:00
📝 2.7 – Quiz: ML & Deep Learning Checkpoint 🔒
📝 2.8 – Hands-On: Build a Simple Classifier with Teachable Machine 🔒
📝 2.9 – Overfitting, Underfitting, and How to Fix Them 🔒 13:00
📝 2.10 – Section 2 Wrap-Up & Mini-Project Brief 🔒
Section 3: Advanced AI & Practical Applications
10 lessons
📝 3.1 – Natural Language Processing (NLP) 🔒 14:00
📝 3.2 – Computer Vision: How AI Sees the World 🔒 15:00
📝 3.3 – Generative AI: Creating with AI 🔒 14:00
📝 3.4 – Introduction to Python for AI 🔒 17:00
📝 3.5 – Your First AI Program: Linear Regression in Python 🔒 18:00
📝 3.6 – Building an Image Classifier with TensorFlow 🔒 20:00
📝 3.7 – NLP in Practice: Sentiment Analysis Project 🔒 19:00
📝 3.8 – Quiz: Advanced AI Applications 🔒
📝 3.9 – Hands-On: Fine-Tune a Pre-Trained Model 🔒
📝 3.10 – Section 3 Wrap-Up & Capstone Details 🔒
Section 4: Building, Deploying, and Scaling AI
10 lessons
📝 4.1 – Model Deployment: From Notebook to Production 🔒 15:00
📝 4.2 – Building an AI Web App with Flask 🔒 20:00
📝 4.3 – MLOps: Managing AI in Production 🔒 14:00
📝 4.4 – AI Ethics in Practice: Bias Detection & Fairness 🔒 14:00
📝 4.5 – AI and Big Data: Scaling with Cloud & Distributed Computing 🔒 14:00
📝 4.6 – The Future of AI: Trends & Opportunities 🔒 14:00
📝 4.7 – AI Career Pathways & Portfolio Building 🔒 14:00
📝 4.8 – Final Course Quiz Free preview
📝 4.9 – Capstone Project Work Session 🔒
📝 4.10 – Course Wrap-Up & Next Steps 🔒 08:00

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About the Instructor

UI
Utibe Inyang