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Navigating the AI Future: Trends & Skills for 2025

Muhammad Nouman Khan

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ABOUT ME

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Agenda

  1. AI Trends Shaping 2025
  2. Core Skills: Deep Learning, NLP, AI Agents
  3. Ethical AI & Responsible Practices
  4. Free Learning Resources & Certifications
  5. AI Automation Tools for Efficiency
  6. Career Pathways & Niche Opportunities
  7. Q&A + Your Journey in AI

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Why AI Matters in 2025

  • Quote: “AI is the new electricity” – Andrew Ng
  • Key Stats:
    • AI market to hit $1.8T by 2030 5.
    • 85% of businesses will adopt AI by 2025 3.
  • Impact: Healthcare, climate tech, education, and beyond.

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Timeline

1760s

2010s

1990s

2020s

2025

1950s

Rule Based Systems

Machine Learning and Intelligent Agents

Deep Learning Revolution

Gen AI

Agentic AI Era

Turing Test

ELIZA - the first chatbot, Expert systems, Backpropagation

Alan Turing proposes the Turing Test, Introduces the Perceptron

AlexNet wins the ImageNet challenge, DeepMind’s AlphaGo defeats Go champion Lee Sedol

 IBM’s Deep Blue defeats chess champion Garry, launches ImageNet

I systems that operate autonomously, collaborate, and adapt to complex environments

ChatGPT, Stable Diffusion, Mid-Journey, Llama, Gemini, Whisper …

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Latest AI Trends for 2025

Autonomous systems handling multi-step workflows (e.g., scheduling, coding).

Agentic AI

Combining text, images, and voice (e.g., diagnosing car issues via photos).

Multimodal AI

Democratizing access (e.g., Meta’s Llama, Deepseek).

Open-Source AI

Solving complex problems 100Mx faster.

Quantum AI

Green data centers and AI-driven climate solutions.

Sustainable AI

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AI Agents: The Future of Automation

Types of Agents:

Simple Reflex Agents

Goal-Based Agents

Learning Agents

Multi-Agent Systems (MAS)

Hierarchical Agents

Hybrid Agents

Definition: Autonomous systems that learn, adapt, and act (e.g., self-driving cars, customer service bots) 

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How can you begin your AI journey?

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Build a Strong Foundation

  • Programing language: (Python, JavaScript)
  • Basic Libraries: Libraries like NumPy, Pandas, and Matplotlib.
  • Machine Learning: (scikit-learn)
  • Deep Learning: (TensorFlow and PyTorch)
  • Natural Language Processing: (RNN, LSTM, Transformers)
  • Reinforcement Learning
  • GENAI onwards 🡪

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Development Side

NETWORKING

FAST API

FLASK

DJANGO

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Latest AI Development

CODING SIDE:

  • Understand LLMs and use it via programing
  • Create Chatbots, Agents, RAGs.
  • TOOLS:
    • Langchain
    • Llama Index
    • Crew AI
    • AutoGen
    • PyData

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Latest AI Development

NO CODE – LOW CODE:

  • MAKE
  • GoHighLevel
  • Zapier
  • N8N

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Automation via n8n

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How to Stay Ahead

  • Newsletters
  • Social Media Channels
  • Follow Leading AI Companies updates
  • Discussions
  • Courses
  • Follow Industry Leaders: Andrew Ng, Yann LeCun, OpenAI Blog.
  • Join Communities: Kaggle, GitHub, AI subreddits.

PRATICE – PRATICE - PRATICE

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Scenarios

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Scenario 1

A food company aims to automate its order-taking process using AI, replacing the need for human operators to answer calls and take orders manually.

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Scenario 2

An e-learning platform seeks to enhance student learning by incorporating real-time visualizations and advanced teaching methods.

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Scenario 3

A client want to make an Application for language learning, in which an AI will talk to you and correct your mistakes while conversation in learning language

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RESOURCES

YOUTUBE Videos

Deeplearning.ai Short Courses

More

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Contact:

    • LinkedIn: www.linkedin.com/in/muhammad-nouman-khan-248530233
    • GitHub: https://github.com/iammuhammadnoumankhan

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AI won’t replace you, but someone using AI will.