For those interested in AI chatbot technology
Discover how AI can transform the way you work, think, and create with Master ChatGPT in Research, Science and Engineering. This hands-on course empowers you to leverage cutting-edge tools like ChatGPT, Perplexity AI, and Gemini AI to streamline research, solve real-world problems, and produce professional-quality documents with ease. Whether you’re a student, scientist, or professional, you’ll gain practical skills to enhance productivity, think critically about AI outputs, and thrive in today’s technology-driven world. Join us and unlock the power of AI to achieve more, faster—don’t miss your chance to lead the way in the AI revolution!
What you’ll learn
- Learn about the current terminology, uses and possibilities of ChatGPT and other similar AI tools like perplexity AI.
- Work Across Diverse Fields: Practical AI applications in engineering, law, academia, and business.
- Time Management and Productivity: Use AI to save time and focus on what matters most in your studies or career..
- Adapt AI for Personalized Needs: Tailor AI solutions to suit your specific academic or professional goals..
Course Content
- Overview and content –> 2 lectures • 15min.
- Introduction –> 4 lectures • 16min.
- ChatGPT –> 7 lectures • 24min.
- Caution with AIs –> 3 lectures • 8min.
- Who trains the AI and how is it trained? –> 2 lectures • 7min.
- Some useful tricks –> 1 lecture • 2min.
- Practical examples using AI chatbots to solve all sorts of problems –> 11 lectures • 1hr 5min.
- Questions and answers –> 1 lecture • 1min.
Requirements
Discover how AI can transform the way you work, think, and create with Master ChatGPT in Research, Science and Engineering. This hands-on course empowers you to leverage cutting-edge tools like ChatGPT, Perplexity AI, and Gemini AI to streamline research, solve real-world problems, and produce professional-quality documents with ease. Whether you’re a student, scientist, or professional, you’ll gain practical skills to enhance productivity, think critically about AI outputs, and thrive in today’s technology-driven world. Join us and unlock the power of AI to achieve more, faster—don’t miss your chance to lead the way in the AI revolution!
Contents (for this course 1 to 6, next coming course (part 2) includes section 7)
1 What are AI chatbots or Generative AI (GenAI) Chatbots ?
1.1 ChatGPT
1.2 Beyond ChatGPT: Perplexity AI and Gemini AI
Initial considerations
2. ChatGPT
2.1 ChatGPT
2.2 ChatGPT what is ChatGPT?
2.2.1 LIMITATION 1. Incorrect or nonsensical answers
2.2.2 LIMITATION 2. Tweaks and input phrasing
2.2.3 LIMITATION 3. Review and feedback
2.2.4 LIMITATION 4. Methods
2.3 Example: differences with typical resources
2.4 The problem of the source
OpenAI as the main source to learn about OpenAI
3. Caution: Ethical standards and example of bias
3.1 The absolutely right loophole: example
4. Fundamental concepts
4.1 Human demonstrator
Human demonstrator: Supervised Learning
Human demonstrator: Reinforcement
4.2 AI trainer
5. Useful tricks
Using ChatGPT to learn about ChatGPT
Asking ChatGPT if it can do something
6 EXAMPLES
6.1 Example: generic ChatGPT use for coding
What happens now within this “Chat”
6.2 Example: coding routines
6.3 Example: bypassing what the GenAI can’t do
6.4 Exercises or exams
6.5 Example: using GenAIs in parallel
6.6 Example social media and promotion
6.7 Example: engineering – plumbing
6.8 Example: assessing the feasibility of a project
6.9 Example: electrical engineering/cable design
6.10 Example: local engineering regulations
Examples in section 7 ( not included in the present course but included in the coming second part).
7. Examples in science and research
7. 1 Example: The driven oscillator
7.1.2 Codes in python, Matlab, Octave and C
7.2 Example: the relevance of knowing concepts
7.3 Example: a machine learning case
7.4 Example: magnetism in the nanoscale
7.5 Example: summarizing a scientific paper
7.6 Redoing and improving a text
7.7 Example of ChatGPT in law
Appendix: learning directly from the source
Appendix: Reinforcement Learning from Human Feedback