AI Fundamentals and Practical Applications

Jul 16, 2024

Class Lecture Journey: Understanding Artificial Intelligence ЁЯза

Key Points of the Lecture

Objective:

  • Understanding Tools: Basic knowledge of AI tools that can be used in business development.
  • Applications: Practical uses of AI and their capabilities.
  • Client Dealing: Clear nomenclature of AI to effectively communicate with clients.

Main Points:

  • General Knowledge of AI: Explained the difference between AI, Narrow AI, and General AI.
  • Introduction of Tools: What types of tools are available in the market and how to use them.
  • Practical Exercises: Emphasized the importance of live practical exercises.

Sectors of AI:

  • Narrow AI (NI): Where basic human thinking processes are being replaced.
  • General AI (GAI): Where machines are capable of thinking and working like humans.
  • Impact on Society and Business: Highlighted the current and future impact of AI.
  • Applications in Fields: Use of AI in various fields such as Medical, Agriculture, Banking, Education, etc.
  • Digital Marketing: How performance can be enhanced using AI.

Concepts:

  • Model Training: How models are trained, the importance of training data, and testing data.
  • API: The functions of API and common use cases.
  • Prompt Engineering: How to ask effective questions to obtain correct and useful information.
  • Challenges: The need for data verification and validation.

Preparation and Practical Applications:

  • Tool Utilization: Use of various AI tools and integration into the work.
  • Projects: Learning through live projects and assignments.
  • Final Presentation: Giving a practical presentation of learnings at the end of 4 months.

FAQs:

  • Supervised and Unsupervised Learning: Explained in detail along with their applications.
  • Labeled Data: Concept of labeled and unlabeled data and their practical applications.
  • Digital Marketing: Improvement in freelancing through AI and prompt engineering.
  • Comparative Models: Information about various AI models.

Motivational Thoughts:

  • Passion for Learning: The need to learn AI and adopting a practical approach for it.
  • Working in Groups: The importance of collaboration and helping each other.