Beginner Course to Artificial Intelligence

This beginner-friendly AI course helps you understand how Artificial Intelligence works in a simple and practical way. You will learn Python, algorithms, neural networks, NLP, machine learning, and real-world AI uses through easy lessons and weekly hands-on labs. Each module includes small projects like building a chatbot, creating smart maps, analyzing data, scraping websites, and trying popular AI tools.

By the end of the course, you will create your own AI project that proves your skills and gives you the confidence to move forward in your learning or career.

Format

Remote

Level

Begineer

Access

Subscription

Duration

32 Hours

Recognition

Certificate of Completion

Price

15,000 PKR 20,999 40% Off

About the Course

This course helps you understand the world of Artificial Intelligence in a simple and practical way. It is made for beginners who want to learn how AI works and how it is used in real life.

Course Overview

In this AI course, you will learn the key concepts of Artificial Intelligence through clear lessons and weekly hands-on labs. You will explore how AI makes decisions, how machines learn from data, how chatbots understand language, and how simple neural networks work. The course also covers planning, prediction, data analysis, and real AI applications used today in industries like healthcare, security, and automation.

You will complete useful projects such as building a chatbot, scraping websites, creating smart maps, analyzing real datasets, and using popular AI tools. Everything is taught in simple steps so learners with no background can easily understand and apply the ideas.

Course Outcomes

By the end of this course, you will be able to:

  • Understand AI basics, including reasoning, NLP, machine learning, and neural networks.
  • Use Python to create simple AI programs and small working projects.
  • Build useful tools like chatbots, data visualizations, and web scrapers.
  • Work with real datasets and understand how AI is used in real-world situations.
  • Complete a final project that shows your skills and can be added to your portfolio.

Career Path

This course helps you build strong beginner-level AI skills that are useful in many roles. It is great for students, beginners, job seekers, or professionals who want to understand how AI works so they can use it in their field.

AI skills are in high demand across many areas like marketing, IT, customer service, data roles, and business operations. Learning AI basics opens the door to more advanced paths such as machine learning, data science, NLP engineering, or cloud-based AI roles in the future.

This course gives you the right start to move toward higher-level AI and cloud careers with confidence.

Course Outline

Module 1: Introduction to Artificial Intelligence (Week 1)

Topics:

  • What is Artificial Intelligence?
  • History and evolution of AI
  • Importance and applications of AI in daily life
  • Difference between AI, ML, and Deep Learning

Lab:

  • Install Python & Jupyter Notebook
  • Write your first “Hello AI” Python program
  • Create a simple AI decision-making example (if/else-based reasoning)

Module 2: Algorithms and Neural Networks (Week 2)

Topics:

  • Understanding algorithms and their role in AI
  • Introduction to neural networks (basic concepts)
  • How AI systems “learn” through data

Lab:

  • Create a simple prediction algorithm using Python
  • Build a very basic neural network simulation (using lists or NumPy)

Module 3: Core Parts of Artificial Intelligence (Week 3-4)

Week 3 – Reasoning & NLP
Topics:

  • Introduction to AI Reasoning
  • Natural Language Processing (NLP) overview
  • How AI understands human language

Lab:

  • Create a simple chatbot using Python
  • Perform basic text analysis (word count, sentiment check using TextBlob)

Week 4 – Planning & Machine Learning (ML)
Topics:

  • What is AI Planning?
  • Introduction to Machine Learning
  • Supervised vs. Unsupervised Learning

Lab:

  • Build a basic ML model using scikit-learn
  • Train and test a simple dataset (e.g., Iris dataset)

Module 4: Development and Use Cases of AI (Week 5)

Topics:

  • AI applications across industries
  • AI in speech recognition, facial recognition, healthcare, and robotics
  • Ethical implications of AI

Lab:

  • Explore an open-source AI API (like HuggingFace or OpenAI demo)
  • Case Study discussion: How AI is used in healthcare diagnostics

Module 5: AI Project Development (Week 6–8)

Week 6 – AI Dictionary with Python
Lab Project:

  • Build a Python program that gives word meanings and pronunciation using an API
  • Add voice interaction (optional)

Week 7 – Web Map of Volcanoes and Population (AI + Python)
Lab Project:

  • Use Folium library to create an interactive world map
  • Highlight volcanoes and population data
  • Apply AI logic to color-code based on risk levels

Week 8 – Data Analysis + Web Scraping Project
Lab Project 1:

  • Data Analysis using Pandas & Matplotlib (e.g., COVID data visualization)

Lab Project 2:

  • Web Scraping with BeautifulSoup4
  • Extract live data (e.g., news headlines, job listings)

Final Project (Week 8)
Title:

  • AI-Powered Real-World Application

Options:

  • Mini Chatbot with NLP
  • Population Density Map
  • AI-based Sentiment Analyzer

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