Course Code: introdeepseek
Duration: 14 hours
Prerequisites:
  • An understanding of basic computer operations
  • No prior experience with AI

Audience

  • IT professionals curious about AI
  • Business professionals exploring AI applications
Overview:

DeepSeek is an LLM (large-language-model) AI platform that provides a service similar to products like ChatGPT.

This instructor-led, live training (online or onsite) is aimed at beginner-level participants who wish to understand DeepSeek's architecture and usage.

By the end of this training, participants will be able to:

  • Understand the basic concepts of AI and LLMs.
  • Explore DeepSeek's architecture and its use cases.
  • Apply foundational AI concepts to real-world scenarios.
  • Gain insights into ethical considerations in AI development.

Format of the Course

  • Interactive lecture and discussion.
  • Lots of exercises and practice.
  • Hands-on implementation in a live-lab environment.

Course Customization Options

  • To request a customized training for this course, please contact us to arrange.
Course Outline:

Introduction to Artificial Intelligence

  • What is AI? History and evolution
  • OpenAI ChatGPT, Google Gemini, Microsoft Copilot, etc.

DeepSeek Overview

  • What is DeepSeek? Key features and capabilities
  • DeepSeek's architecture and components
  • Applications of DeepSeek in various industries

AI Concepts

  • Data preprocessing and feature engineering
  • Model training and evaluation

DeepSeek Use Cases

  • Text generation and summarization
  • Sentiment analysis and classification
  • Real-world examples of DeepSeek in action

Ethical AI and Responsible Use

  • Understanding bias in AI models
  • Ethical considerations in AI development
  • Best practices for responsible AI use

Hands-on Exercises

  • Exploring DeepSeek's interface and tools
  • Building a simple AI model using DeepSeek
  • Analyzing and interpreting model outputs

Future Trends

  • Emerging trends
  • DeepSeek's role in the future of AI
  • Opportunities for further learning and specialization

Summary and Next Steps

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