Practical Guide to AI & ML: Mastering Future Tech Skills
What you'll learn
- Demonstrate a solid understanding of the difference between AI, Machine Learning and Deep Learning.
- Clearly articulate why Large Language Models like ChatGPT and Bard are NOT intelligent.
- Articulate the difference between Supervised, Unsupervised, and Reinforcement Machine Learning.
- Explain the concept of machine learning and its relation to AI.
- Define artificial intelligence (AI) and differentiate it from human intelligence.
- Describe what Artificial Intelligence is, and what it is not.
- Explain what types of sophisticated software systems are not AI systems.
- Describe how Machine Learning is different to the classical software development approach.
- Compare and contrast supervised, unsupervised, and reinforcement learning.
- Explain Supervised and Unsupervised Machine Learning terms such as algorithms, models, labels and features.
- Explain Function Approximators and the role of Neural Networks as Universal Function Approximators.
- Explain Encoding and Decoding when using machine learning models to work with non-numeric, categorical type data.
- Demonstrate an intuitive understanding of Reinforcement Learning concepts such as agents, environments, rewards and goals.
- Identify examples of AI in everyday life and discuss their impact.
- Evaluate the effectiveness of different AI applications in real-world scenarios.
- Apply basic principles of neural networks to a hypothetical problem.
- Discuss the role of data in training AI models
- Construct a neural network model for a specified task
- Assess the impact of AI on job markets and skill requirements
- See an end-to-end, supervised machine learning process to tackle a regression problem, using Microsoft's Model Builder and ML .Net.
- Understand the tasks and activities that take place behind the scenes. From data preparation all the way to model training and evaluation.
- Understand data transformation, feature scaling, iterating through algorithms, evaluation metrics, overfitting, cross-validation and regularization.
- Understanding the impact of evaluation metrics on model performance, and how to check for overfitting.
- Understand the lasting fundamentals of machine learning that are independent of the tools or platforms one can use.
- Gain a deep understanding of machine learning concepts by seeing them in action, during a practical machine learning demonstration.
- Understand the importance of Exploratory Data Analysis (EDA) and the impact that the statistical distribution of the data has on model performance.
- Learn how to set up Visual Studio and to configure it to enable Model Builder, the graphical tool that will be used to demonstrate the machine learning process.
- Learn how to use Model Builder to train models without having to code.
Requirements
- There are no requirements or prerequisites for this course, but the items listed below are a guide to useful background knowledge that will increase the value and benefits of this course:
- High school Math and a deep interest in machine learning would be highly beneficial for this series of lessons. There is no coding or complex mathematics involved in this course. If you can't remember high-school math, it will not prevent you from learning the concepts in this course.
- An appreciation for, but not a deep knowledge of, the importance of Mathematics and Statistics in Machine Learning.
- Basic computer literacy, including familiarity with operating a computer.
- A basic understanding of supervised machine learning is required. The student would at the very least need to understand what regression is, what features are, and what it means for a model to be trained to fit a function to input features in order to predict labels.
- The student needs to have a Windows machine with a few GB of free disk space to install Visual Studio, in order to replicate the machine learning process I will demonstrate. However, this is not essential.
- A Windows machine is ideal, but a student with a Mac will still be able to follow along. The course content is visual enough to demonstrate the concepts, without the student having to physically do the machine learning exercise.
Description
Unlock the Future: Dive into the World of AI and ML!
Welcome to an extraordinary journey into the realms of Artificial Intelligence and Machine Learning. Led by AI and Technology expert Irlon Terblanche, this course is not just an educational experience; it's an adventure into the technologies shaping our future. Whether you're a curious beginner, a business leader, or an aspiring tech guru, this course promises to transform your understanding of some of the most cutting-edge topics in tech.
Why This Course?
Designed for Curiosity and Career: Tailored for both personal and professional growth, this course demystifies AI and ML, making them accessible to everyone. It's perfect for busy professionals, entrepreneurs, and anyone with a thirst for knowledge.
No Math Fears: We've designed the course to be inclusive, requiring no prior expertise in math or coding. It's all about understanding concepts in a friendly, approachable manner.
Lifetime Access and Flexible Learning: Learn at your pace with full lifetime access to all resources, including videos, articles, and downloadable materials.
What You'll Achieve:
Grasp the Core Concepts: Understand the difference between AI, ML, and Deep Learning. Learn what sets them apart and how they're revolutionizing industries.
Debunk Myths: Discover why systems like ChatGPT aren't truly intelligent and explore the limitations of current AI technologies.
Practical Skills: Gain hands-on experience with tools like Microsoft's Model Builder and ML .Net. Understand the complete machine learning process, from data preparation to model evaluation.
Real-World Applications: See how AI and ML are being applied in various sectors. Discuss their impact on job markets and skill requirements.
Course Highlights:
Engaging Video Lectures: Over 4 hours of high-quality, engaging video content that breaks down complex ideas into digestible segments.
Comprehensive Topics: From the basics of neural networks to the intricacies of supervised and unsupervised learning.
Practical Demonstrations: Learn by doing with practical exercises and demonstrations.
Dynamic Learning Resources: An article and a downloadable resource to complement your learning journey.
Mobile and PC Access: Learn on the go or from the comfort of your living room.
Course Structure:
The course is divided into 9 comprehensive sections, each designed to build upon the last, ensuring a smooth learning curve. Starting with an introduction to AI and ML, it moves through various topics like function approximation, neural networks, and deep learning, concluding with practical demonstrations of machine learning in action.
Enroll Now and Transform Your Understanding of AI and ML!
Join us on this captivating journey into AI and ML. With Irlon Terblanche's expert guidance, engaging content, and practical insights, you're not just learning; you're preparing for the future. Enroll today and be part of the AI revolution!
Who this course is for:
- Business Executives and Managers: Professionals in leadership roles who are looking to understand how AI can be leveraged for strategic advantage in their organizations.
- Busy professionals who need a short, easy but solid understanding of AI fundamentals.
- Entrepreneurs and Startup Founders: Individuals who are building or planning to build businesses where AI could play a transformative role.
- Technology Consultants and Advisors: Professionals who provide strategic advice on technology adoption and integration.
- Absolute beginners who are aspiring to become Data Scientists or Machine Learning Engineers, and who are looking for the best fundamentals of artificial intelligence and machine learning.
- Product Managers and Developers: Those who are involved in product development and are interested in incorporating AI into new or existing products.
- Non-technical Professionals: Including, but not limite to Business Analysts or Marketers. Yhis course can give you all the skills you need to be able to interact with Data Scientists, Machine Learning Engineers or other AI specialists.
- AI and machine learning enthusiasts: This course will still be valuable because it covers extremely important fundamental concepts that are often misunderstood.
- This course is not for you if you have an aversion or intense dislike for Mathematics.
- Also, if you are looking for coding tips, technical detail about the different machine learning algorithms, back-propagation in Neural Networks, loss functions, gradient descent, policy gradient methods, etc., then these series of lessons are definitely not for you.
- This course is for entry-level machine learning enthusiasts, who have had some kind of theoretical introduction to machine learning, but who wants to put the theory into practice.
- Machine learning enthusiasts who do not have a background in Statistics, Data Science or programming, but who want to see the complexities of machine learning in practice.
- Machine learning enthusiasts who want to learn about complex concepts by seeing them in action, rather than by seeing a presentation.
- Technical beginners who want to learn solid machine learning fundamentals before progressing onto more advanced courses where a detailed knowledge of statistics, calculus and programming may be required.
Instructors
- 4.4 Instructor Rating
- 62,560 Reviews
- 420,745 Students
- 294 Courses
"What an amazing course! After finishing this course, I have confidence. Thank so much Dr Peter Alkema" ... "This is exactly the jump-start I needed. Very clear and concise"
I lead Digital Transformation & Architecture at ABB and I've been featured on CNBC Africa and won the Gartner CIO Of The Year in 2016. I founded and led the largest banking hackathon in South Africa which was published in 2019 as a case study by Harvard Business School.
I've taught over 100,000 students about technology, business, academics and self-development. In 2020 I completed my PhD at Wits University In Johannesburg. The study introduced a ground-breaking theory of Agile software development teams. My woodworking book was published in 2014 and has sold over 10,000 copies.
Olugbenga Gbadegesin: "Excellent delivery" / Lebogang Tswelapele: "This is what I have been longing for" / Paskalia Ndapandula: "Peter speaks with so much clarity" / Amantle Mangwedi: "It was straight to the point and the sections are cut into nice short segments which made it easier to go through" Kathy Bermudez: "Excellent material. Well organized..."
Werner van Wyk: "Thank you Peter, once again your lesson and course have given me so much knowledge and understanding" / Yvonne Rudolph "I really look forward to take everything i learned in action" / Josephine Mahlangu: "exactly what I needed to know, absolutely valuable and helpful for my personal growth"
- 4.4 Instructor Rating
- 5,866 Reviews
- 26,510 Students
- 45 Courses
Hi there! I'm Irlon Terblanche, a seasoned CEO, management consultant, and technologist, leveraging a rich background in Bitcoin, banking, investments, and technology to revolutionize how we approach education and financial abundance for everyone. My journey began with an Electromechanical Engineering degree from the University of Cape Town, bolstered by an MBA. In parallel with maintaining C-level corporate roles, including CEO positions in the banking, investments and insurance sectors, I've honed my skills in full-stack development, machine learning, cybersecurity and Bitcoin. I am well-versed in global monetary and economic policy matters.
My passion for continuous, hands-on learning and innovation in the tech space drives my courses. I aim to simplify complex concepts, drawing from a deep and foundational understanding of concepts in engineering, financial markets, and technology. Join me to gain foundational insights and skills that will empower your journey in the evolving world of technology and finance. Let's explore the endless possibilities together!