Course Overview
- Duration: 6-12 Weeks.
- Delivery Mode: Classroom / Online / Hybrid
- Course Level: Beginner to Advanced
- Language: Hindi/English (as per student preference)
- Target Audience: Students, Professionals, Freelancers, Entrepreneurs, Housewives
- Flexible learning: Online, Offline.
📚 Course Modules
🧠 Module 1: Introduction of Artificial Intelligence
Overview
This module introduces the core concepts of Artificial Intelligence, covering its history, development, types, and real-world applications.
Key Topics
- 1. Definition and scope of AI
- 2. History and evolution of AI
- 3. Goals and capabilities of AI
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Types of AI:
- (i) Narrow AI – Task-specific intelligence (e.g., chatbots, recommendation engines)
- (ii) General AI – Human-like reasoning and cognition (theoretical)
- (iii) Super AI – Intelligence surpassing human capabilities (hypothetical)
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Applications across industries:
Healthcare, finance, robotics, transportation, marketing
📊 Module 2: Machine Learning Essentials
Overview
This module focuses on the fundamentals of Machine Learning (ML), a subfield of AI that enables systems to learn from data and improve over time without being explicitly programmed.
Key Topics
- 1. What is Machine Learning?
- 2. The role of data in ML
- 3. ML development lifecycle
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4. Types of Machine Learning:
- (i) Supervised Learning
- (ii) Unsupervised Learning
- (iii) Reinforcement Learning
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5. Core ML algorithms:
- (i) Linear & Logistic Regression
- (ii) Decision Trees and Random Forests
- (iii) Support Vector Machines (SVM)
- (iv) K-Nearest Neighbors (KNN)
- (v) Naïve Bayes
- (vi) Basics of Neural Networks
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Applications across industries:
Healthcare, finance, robotics, transportation, marketing
🔬 Module 3: Deep Learning and Natural Language Processing
Overview
This module explores advanced ML techniques through Deep Learning and provides practical insights into Natural Language Processing (NLP), enabling interaction with human language.
Key Topics
- 1. Deep Learning
- Introduction to Neural Networks
- Deep Neural Network architectures
- Convolutional Neural Networks (CNNs)
- Recurrent Neural Networks (RNNs)
- Transfer Learning and Pre-trained Models
- 2. Frameworks and Tools:
- TensorFlow
- PyTorch
- Keras
- 3. Natural Language Processing (NLP)
- Text preprocessing: Tokenization, stemming, lemmatization
- Named Entity Recognition (NER)
- Sentiment analysis
- Text classification
- 4. Language models: GPT, BERT, LLaMA, Claude
🖼️ Module 4: Computer Vision and AI Development Tools
Overview
This module introduces Computer Vision, a field of AI that enables machines to interpret visual data, and provides hands-on experience with essential tools and libraries.
Key Topics
- 1. Computer Vision
- Image classification
- Object detection
- Facial recognition
- Image segmentation
- OCR (Optical Character Recognition)
- 2. Development Tools and Technologies
- Programming Languages: Python, R
- Libraries: Scikit-learn, NumPy, Pandas, OpenCV
- Platforms: Google Colab, Jupyter Notebook, AWS SageMaker
⚖️ Module 5: Ethics, Fairness, and Responsible AI
Overview
This module addresses the ethical, legal, and societal considerations of AI systems to ensure responsible development and deployment.
Key Topics
- 1. Ethical principles in AI design
- 2. Algorithmic bias and fairness
- 3. Data privacy and protection
- 4. Explainability and transparency
- 5. Accountability in AI decisions
- 6. Regulatory frameworks and compliance: GDPR, EU AI Act, industry standards
🚀 Module 6: Future of AI and Career Opportunities
Overview
Participants explore cutting-edge AI trends and how AI is shaping the future of work, along with detailed insights into career paths and required skills.
Key Topics
- 1. Emerging trends in AI:
- Generative AI
- Edge AI
- AI in Internet of Things (IoT)
- Autonomous systems and robotics
- 2. Career opportunities:
- AI Engineer
- Machine Learning Engineer
- Data Scientist
- NLP Specialist
- AI Product Manager
- Computer Vision Engineer
- 3. Portfolio building and certifications
- 4. Resume and interview preparation for AI roles
🎨 Module 7: AI Tools for Creativity and Productivity
Overview
This practical module highlights a range of modern AI-powered tools that enhance content creation, design, business operations, and productivity.
Key Topics
- 1. Chat and Writing Tools: ChatGPT, Google Gemini, Notion AI, Writesonic
- 2. Image and Video Generation: Bing Image Creator, Leonardo AI, Runway ML, Pictory
- 3. Audio and AI Search: ElevenLabs, Murf.ai, Perplexity.ai, You.com
- 4. Business and Workflow Tools: ChatGPT for Sheets, Tome, Beautiful.ai, Zapier AI
🎓 Course Completion and Certification
Outcomes
Upon successful completion of the course, learners will:
- 1. Gain practical knowledge of AI, ML, Deep Learning, NLP, and Computer Vision
- 2. Be able to build, evaluate, and deploy basic AI and ML models
- 3. Understand ethical and responsible AI practices
- 4. Use industry-relevant tools and platforms
- 5. Receive a Certificate of Completion
Certification
- ✅ Get a Certificate of Completion
- ✅ Build a real-world Capstone Project Portfolio
- ✅ Receive personalised career and freelancing guidance
- ✅ 100% Job Assistance
