Internship - Deep-Dive - GENAI-Technologies
in Internship ProgramAbout this course
What You will Learn?
- Introduction to AI and Machine Learning.
- Natural Language Processing (NLP).
- Generative AI Models.
- Chatbot Fundamentals.
- Natural Language Understanding (NLU).
- Dialogue Management.
- Response Generation.
- Platform Selection.
- Data Preparation.
- Model Training and Fine-tuning.
- Deployment and Integration.
- Ethical Considerations in AI.
- Prompt Engineering.
- Multimodal AI.
- Future of AI Chatbot.
Benefits of Participation:
- Certificate of Completion: Showcase your new skills with an official internship certificate.
- Real-world Experience: Build your portfolio with two Capstone Projects worth INR 6000.
- Career Boost: Leverage 20+ professional Resume Templates to land your dream job.
- Cloud Credits: Explore the power of Microsoft Azure with your INR 8400 cloud voucher.
This intensive program will equip you with the skills to harness the power of AI and build intelligent chatbots in just four weeks. Learn to design and develop chatbots that can understand and respond to natural language, process complex queries, and provide valuable information and services. Master essential techniques for creating engaging and efficient chatbot experiences across various platforms and industries.
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1. Basic concepts, types of AI, and real-world applications.
2. Introduction to machine learning, supervised vs. unsupervised
learning.
1. Text preprocessing techniques (tokenization, stemming,
lemmatization).
2. Text classification and sentiment analysis.
3. Text generation and language modeling.
1. Understanding generative models, autoregressive models, and
diffusion models.
2. Overview of popular models like GPT-3, Stable Diffusion, and Mid
journey.
1. Types of chatbots (rule-based, AI-powered).
2. Chatbot architecture and components (intent recognition, entity
extraction, response generation).
1. Intent classification and entity extraction techniques.
2. Using NLU frameworks like Rasa or Dialogflow.
1. State tracking and context management
2. Designing engaging and informative chatbot conversations
1. Text generation techniques for generating human-like responses.
2. Leveraging large language models for advanced response generation.
1. Evaluating platforms like Dialogflow, Microsoft Bot Framework, or custom development.
2. Data Preparation .
3. Collecting and cleaning training data.
4. Creating training datasets for intent classification and entity
extraction
1. Training language models on domain-specific data.
2. Fine-tuning pre-trained models for specific chatbot tasks.
1.Deploying chatbots on various channels (web, mobile apps,
messaging platforms).
2. Integrating chatbots with other systems (CRM, ERP).
1. Bias and fairness in AI models.
2. Responsible AI development and deployment.
