Level: Beginner to Intermediate
Prerequisites: Basic knowledge of programming (preferably Python) and mathematics (algebra, logic)
Software/Tools Required: Python (Anaconda/Jupyter), Google Colab, scikit-learn, TensorFlow (introductory), AI simulators/tools
Certification: Certificate of Completion from Thakral Global Learning + Preparation for IT Specialist: Artificial Intelligence Certification
📖 Course Overview:
This course introduces students to the fundamental concepts, technologies, and applications of Artificial Intelligence. Designed for aspiring AI professionals, students, and technology enthusiasts, it covers essential areas like machine learning, natural language processing, computer vision, and intelligent agents. It also prepares learners for the globally recognized IT Specialist: Artificial Intelligence certification offered by Certiport/Pearson.
✅ Learning Outcomes:
By the end of the course, learners will be able to:
- Understand the history, scope, and applications of AI
- Identify different types of AI: narrow, general, and super AI
- Apply basic machine learning models using Python
- Work with AI components such as NLP, computer vision, and chatbots
- Understand ethical issues in AI deployment
- Prepare effectively for the AI Certification exam
🧩 Course Modules:
Module 1: Introduction to Artificial Intelligence
- What is AI? History and evolution
- Types of AI: reactive, limited memory, theory of mind, self-aware
- AI vs. Machine Learning vs. Deep Learning
- Real-world applications: healthcare, robotics, finance, retail
Module 2: Fundamentals of Machine Learning
- Supervised, unsupervised, and reinforcement learning
- Datasets, features, labels, and models
- Linear regression and classification basics
- Hands-on: Simple ML model using scikit-learn
Module 3: Working with Data for AI
- Data collection, cleaning, and preparation
- Understanding bias and fairness in datasets
- Exploratory Data Analysis using pandas and matplotlib
- Data splitting: training, validation, and testing
Module 4: Neural Networks & Deep Learning (Intro)
- Basic neural network structure (neurons, layers, activation functions)
- Concept of backpropagation and training
- Use of TensorFlow/Keras for building basic neural networks
- Hands-on: Building a digit recognizer with MNIST dataset
Module 5: Natural Language Processing (NLP)
- What is NLP? Applications in chatbots, translation, sentiment analysis
- Text preprocessing: tokenization, stemming, stop words
- Simple sentiment classifier using NLP libraries (NLTK/spaCy)
- Building a chatbot with basic AI
Module 6: Computer Vision (Intro)
- Image classification and object recognition
- How AI “sees” – image to data conversion
- Using OpenCV and TensorFlow for image tasks
- Hands-on: Face detection or image filter project
Module 7: Ethical AI and Social Implications
- AI bias and fairness
- Job automation and economic impact
- Data privacy, surveillance, and decision accountability
- Responsible AI development principles
Module 8: Capstone Project and Certification Prep
- Project options:
- AI Chatbot for customer service
- Image classifier for product recognition
- Sentiment analysis for social media posts
- Final presentation and feedback
- Review of Certiport AI certification structure and sample questions
- Mock test and exam readiness
📝 Assessment & Evaluation:
- Weekly practical assignments and quizzes
- Two mini-projects based on real-world AI tasks
- Final capstone project presentation
- Mock certification test aligned with Certiport AI exam
💼 Career Pathways:
- AI/ML Developer (entry-level)
- Data Analyst / Junior Data Scientist
- AI Research Assistant
- Chatbot/Voice Assistant Developer
- AI Support Engineer
🌟 Why Choose This Course at Thakral Global Learning?
- Industry-aligned AI curriculum with real-world projects
- Hands-on experience with Python, ML, NLP, and CV
- Prepares you for IT Specialist: Artificial Intelligence Certification
- One-on-one mentoring and post-course support
- Certification and portfolio to showcase your skills
