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Description

Are you interested in exploring the exciting world of AI and mastering the fundamentals to unlock its full potential?
If that’s the case, you’ve come to the right place!
This
Intro to AI course
begins with the fundamentals—exploring the core components behind today's cutting-edge AI algorithms. Through this comprehensive journey, you'll establish a strong foundation and gain deep insights into AI's workings and applications in product development. You’ll learn about various AI models and understand how businesses can leverage them effectively.
Moreover, the course offers
practical knowledge of AI development and integration into web applications and business products
. Discover job opportunities in the rapidly growing AI field and comprehensively understand the essential tools needed for a lucrative career in this high-demand sector. This
ideal AI introductory course
suits those passionate about the field and eager to explore its potential. It offers valuable insights for business stakeholders and a strong foundation for anyone aiming to start a career in AI.
Few industries will escape disruption from artificial intelligence and its significant technological innovations. Embrace AI to gain a competitive edge and lead your industry with its transformative power.
Our
Intro to AI course
provides foundational AI knowledge and practical insights to seamlessly integrate AI into your workflow. Join the select group that grasps AI’s career and business opportunities and leverages its transformative power.
What sets this AI course apart from other online offerings?
1. Production Quality
Our dedicated team has invested thousands of hours in crafting an exceptional learning experience. We focus full-time on simplifying complex topics and designing an engaging Intro to AI course you’ll enjoy.
2. Instructor Excellence
Ned Krastev (CEO of 365 Data Science) has educated over 3 million students worldwide. His courses rank among the most popular online, and he has delivered training for Fortune 100 companies.
3. Engaging Animations
Our courses utilize storytelling and high-quality animations to help internalize AI concepts—far surpassing simple PowerPoint presentations.
We are so confident that you'll love this course that we're offering a FULL money-back guarantee for 30 days! It's a complete no-brainer, sign up today with ZERO risk and EVERYTHING to gain.
What are you waiting for? Click the 'Buy Now' button and embrace the AI-driven future of tomorrow.
Who this course is for:
This course is for you if you want a great career
The course is also ideal for beginners, as it starts from the fundamentals and gradually builds up your skills

What you'll learn

Understand key Artificial Intelligence concepts and build a solid foundation

Skyrocket productivity using AI

Understand Generative AI and the underlying technology

Grasp the importance of AI ethics

Acquire an understanding of key AI tools

Become acquainted with the top job prospects in the AI field

Requirements

  • You will need a copy of Adobe XD 2019 or above. A free trial can be downloaded from Adobe.
  • No previous design experience is needed.
  • No previous Adobe XD skills are needed.

Course Content

27 sections • 95 lectures
Expand All Sections
1-Getting started
6
1.1-What does the course cover
1.2-Natural vs Artificial Intelligence
1.3-Brief history of AI
1.4-Demystifying AI, Data science, Machine learning, and Deep learning
1.5-Weak vs Strong AI
1.6-Quiz 1
2-Data is essential for building AI
5
2.1-Structured vs unstructured data
2.2-How we collect data
2.3-Labelled and unlabelled data
2.4-Metadata: Data that describes data
2.5-Quiz 2
3-Key AI technique
4
3.1-Machine learning
3.2-Supervised, Unsupervised, and Reinforcement learning
3.3-Deep learning
3.4-Quiz 3
4-Important AI branches
5
4.1-Robotics
4.2-Computer vision
4.3-Traditional ML
4.4-Generative AI
4.5-Quiz 4
5-Understanding Generative AI
10
5.1-The rise of Gen AI: Introducing ChatGPT
5.2-Early approaches to Natural Language Processing (NLP)
5.3-Recent NLP advancements
5.4-From Language Models to Large Language Models (LLMs)
5.5-The efficiency of LLM training. Supervised vs Semi-supervised learning
5.6-From N-Grams to RNNs to Transformers: The Evolution of NLP
5.7-Phases in building LLMs
5.8-Prompt engineering vs Fine-tuning vs RAG: Techniques for AI optimization
5.9-The importance of foundation models
5.10-Buy vs Make: foundation models vs private models
6-Practical challenges in Generative AI
4
6.1-Inconsistency and hallucination
6.2-Budgeting and API costs
6.3-Latency
6.4-Running out of data
7-The AI tech stack
7
7.1-Python programming
7.2-Working with APIs
7.3-Vector databases
7.4-The importance of open source
7.5-Hugging Face
7.6-Hugging Face
7.7-AI evaluation tools
8-AI job positions
3
8.1-AI strategist
8.2-AI developer
8.3-AI engineer
9-Looking ahead
2
9.1-AI ethics
9.2-Future of AI