Welcome to this course! Here, you will find a quick guide to the entire syllabus

Module 1: Fundamentals of Artificial Intelligence (Practical Focus)

• AI in a Nutshell

  • Essential concepts: Machine Learning, Deep Learning, NLP.

  • “Weak” vs. “Strong” AI: focusing on what’s actually useful today.

• Success Cases and Limitations

  • Practical examples (Netflix, IBM Watson) from an implementation and results perspective.

Key Outcome: Become familiar with terminology and foundational concepts to better understand AI tools and how to use them in daily work.

Module 2: Language Models and Practical Differences

• Types of Models

  • GPT-3.5, GPT-4, Bard, Llama, etc.

  • When to use each one: cost, speed, context limits.

• Use Cases

  • Content creation, customer support, text analysis, etc.

  • Model selection depending on task type (simple vs. complex).

Key Outcome: Understand which models exist, their purposes, and how to choose the most suitable one for each situation.

Module 3: In-Depth Prompting

• Prompting Best Practices

  • Structure, context, and examples in prompts.

  • How to reduce ambiguity and get more accurate results.

• Prompt Chaining (Workflows)

  • Sequencing prompts for complex tasks: summarize → generate questions → create content.

  • Real examples applicable to marketing, sales, or business reports.

• Tools for Prompting

  • Apps and extensions to simplify prompt editing and testing (ChatGPT web, plugins, basic IDEs).

Key Outcome: Design and chain prompts to maximize productivity and the quality of responses.

Module 4: Process Automation with AI

• Identifying Automatable Tasks

  • Where to apply AI to save time and resources (e.g., customer service, sales reports, etc.).

• Integration with Automation Tools

  • Zapier, Power Automate: orchestrating data and actions alongside ChatGPT and other models.

  • End-to-end workflows (from data collection to final reporting).

• Agents and Task Delegation

  • Setting up agents that operate with limited autonomy to process and answer queries.

Key Outcome: Learn to orchestrate AI-driven workflows, connect various tools, and delegate parts of the process to AI.

Module 5: Key AI Tools for Productivity

• Tool Overview

  • ChatGPT (text), DALL·E (images), DeepSeek (search), Midjourney, etc.

• Selection and Comparison

  • Factors to consider: user-friendliness, cost, features, integration with other apps.

• Concrete Use Cases

  • Rapid design and prototyping, marketing campaign generation, data report creation, etc.

Key Outcome: Gain a practical catalog of tools and how to apply them at work right away.

Module 6: AI for Quick Decision-Making and Strategy

• AI in Strategic Practice

  • Using AI for analytics and predictions (sales, market trends).

• Step-by-Step Implementation

  • How to outline a short adoption roadmap in a team or project.

  • Presenting results and tips to “sell” the idea internally.

Key Outcome: Learn how to incorporate AI into analysis and planning processes, without delving into ethical or regulatory issues.

Module 7: Advanced Use of Tools and Prompting (Higher Level)

(Replaces the former module on KPIs and impact measurement)

• Advanced Prompting and Practical Hacks

  • Employing “roles” and “personalities” in prompts (e.g., “You are a marketing consultant,” “You are a data analyst”).

  • Handling extensive context (using “continuations,” splitting text into sections).

  • Prompt loops and iterative review: generate → correct → refine.

• Integrating Multiple Tools

  • Linking ChatGPT with search tools (DeepSeek) or images (DALL·E) for more comprehensive projects.

  • Collaborative flows: how a team can share prompts and results efficiently.

• Frameworks and Specialized Libraries (No Complex Coding)

  • Introduction to LangChain, LlamaIndex, and other solutions that orchestrate prompts and data.

  • Basic usage of low-code/no-code platforms to leverage these frameworks (if applicable).

• Real Applications and Challenges

  • Solving a complex practical scenario: creating a small “assistant” that searches for information, summarizes it, and generates a report.

Key Outcome: Elevate prompting and tool integration to the next level, exploring advanced techniques and complex workflows to maximize AI’s value in real projects.