Introduction
As we approach the end of Q2, it's the perfect time to revisit the basics of AI or embark on a new learning journey in this rapidly evolving field. With every Fortune 500 company working on an AI strategy to incorporate cutting-edge capabilities and become a market leader, it's crucial to have a solid understanding of the fundamentals.
If you're looking for bite-sized learning to solidify your understanding without getting bogged down by technical jargons, check out my five-part "AI Concepts Made Easy" series. Beyond prompt engineering, you'll need these basics to learn and keep the concepts sticky when implementing an AI strategy and engaging in meaningful professional conversations.
Here's what you will learn:
1.AI Concepts Made Easy: A Beginner's Guide (Part 1)- Learn the basics of AI, machine learning with supervised and unsupervised learning, and real-world examples.
2. AI Concepts Made Easy: A Beginner's Guide (Part 2) - Introduction to deep learning, generative AI, and the differences between deep learning, generative AI, and machine learning.
3. AI Concepts Made Easy: A Beginner's Guide (Part 3) - Introduction to large language models (LLMs), their challenges, future, and real-world examples.
4. AI Concepts Made Easy: A Beginner's Guide (Part 4) - Introduction to hallucinations in AI systems, how to mitigate them, and use cases for improving enterprise operations.
5. AI Concepts Made Easy: A Beginner's Guide (Part 5) - Introduction to GPUs, and the differences between CPUs and GPUs.
Conclusion
Whether you're a seasoned professional or a curious learner, these basics form the foundation upon which advanced AI strategies are built. By mastering the core principles of AI, machine learning, deep learning, generative AI, large language models, and the critical differences between CPUs and GPUs, you equip yourself with the knowledge to navigate and leverage the AI landscape effectively.
Remember, the journey to mastering AI is ongoing. Stay curious, keep learning, and continue to explore how these technologies can be applied to drive innovation and efficiency in various fields. Thank you for following along with this series, and I hope it has made the world of AI a bit more engaging for you.
Happy learning!