- Personalized 1 to 1 Interactive Program – 99 $ / Hour
- Classroom training - Online Interactive with the batch size of 15 to 20 People
Expert Instructors: Learn from industry experts who have extensive experience in AI architecture and development.
Hands-on Experience: The course emphasizes hands-on learning to reinforce theoretical concepts.
Interactive Learning: Engage in interactive learning experiences through discussions, Q&A sessions, and collaboration with fellow learners.
Flexible Learning Options: The course offers flexibility in terms of learning pace and accessibility.
Real-World Projects: Apply the knowledge and skills acquired throughout the course to real-world projects.
Career Development: Acquire valuable skills that are in high demand in today's job market.
Module 1 :Introduction to Chatgpt &open AI
1.1 Overview of conversational AI and its applications
1.2 Introduction to natural language processing (NLP) and natural language understanding (NLU)
1.3 Understanding the challenges and limitations of conversational AI systems
1.4 Introduction to ChatGPT and its underlying architecture (e.g., transformer models)
1.5 Exploring the capabilities and limitations of ChatGPT
1.6 Fine-tuning ChatGPT with custom datasets
1.7 Introduction to OpenAI API and access to ChatGPT
Module 2 : ChatGPT Model Enhancement Techniques
2.1 Advanced techniques for improving the performance of ChatGPT
2.2 Context window management for longer conversations
2.3 Controlling response generation (e.g., temperature, top-k, top-p sampling)
2.4 Promoting safer and more ethical AI interactions
Module 3 : Data Collection and Annotation for ChatGPT
3.1 Techniques for collecting and preprocessing conversational datasets
3.2 Annotation and labeling guidelines for training ChatGPT
3.3 Addressing biases and handling sensitive content in conversational data
Module 4 : Evaluation and Metrics for Conversational AI
4.1 Metrics for evaluating conversational AI systems (e.g., perplexity, BLEU, human evaluation)
4.2 Challenges in evaluating ChatGPT and other AI models
4.3 Comparative analysis of different evaluation techniques
Module 5 : Multi-Turn Conversations and Dialogue Systems
5.1 Understanding multi-turn conversations and context modeling
5.2 Techniques for building dialogue systems using ChatGPT
5.3 Handling user intents, dialogue state tracking, and system responses
5.4 Reinforcement learning for dialogue management
Module 6 : Knowledge Integration and External APIs
6.1 Integrating external knowledge sources and APIs with ChatGPT
6.2 Utilizing knowledge graphs and ontologies for improved responses
6.3 Querying databases and structured data in conversational AI systems
Module 7 : Advanced Topics in Conversational AI
7.1 Transfer learning and domain adaptation for ChatGPT
7.2 Generation of diverse and creative responses
7.3 Open-domain vs. task-oriented conversational AI systems
7.4 Multilingual and cross-lingual conversational AI
Module 8 : ChatGPT Deployment and System Architecture
8.1 Scalability and performance considerations for ChatGPT deployment
8.2 Designing robust conversational AI systems
8.3 Cloud infrastructure and deployment options
8.4 Handling user authentication, security, and privacy concerns.
Q : Is prior programming experience required for this course?
A: While prior programming experience is not mandatory, having a basic understanding of programming concepts, particularly in languages like Python, is recommended.
Q : What level of AI knowledge is assumed for this course?
A: The course caters to participants with varying levels of AI knowledge, from beginners to those with some prior exposure. It provides a comprehensive curriculum that covers both foundational and advanced topics.
Q : How much time should I allocate for the course each week?
A:The course is designed to be flexible, allowing you to learn at your own pace. The time commitment may vary depending on your learning style and availability, but dedicating several hours per week for lectures, assignments, and projects is recommended.
Q : Will I receive a certificate upon completing the course?
A: Yes, upon successful completion of the course, participants receive a certificate of completion, recognizing their achievement and proficiency in AI architecture and development.
Q : Can I access the course materials after completing the course?
A: The availability of course materials after completion may vary depending on the course platform or provider. It's advisable to check with the course administrators regarding post-course access to materials.
Q : Are there any prerequisites for enrolling in the course?
A: The course recommends basic programming knowledge, and familiarity with Python is advantageous. However, there are no strict prerequisites, and the course is open to anyone with an interest in AI architecture and development.
Q : Will I have access to instructors for guidance and support?
A: Yes, the course provides support from expert instructors who can assist with questions, provide guidance, and offer clarifications throughout the duration of the course.
Q : Are there any opportunities for networking or collaborating with other learners?
A: Yes, the course typically provides a platform for learners to engage in discussions, participate in forums, and collaborate with fellow participants. This fosters networking opportunities and allows for knowledge sharing.
Q : Can I apply the skills learned in this course to real-world projects?
A: Absolutely! The course incorporates real-world projects to provide practical experience and allow participants to apply their skills and knowledge to relevant AI applications.
Q : How will this course benefit my career in AI architecture and development?
A: Completing this course will enhance your knowledge, skills, and proficiency in AI architecture and development. It can open up various career opportunities in industries embracing AI technologies and equip you with the skills in high demand in today's job market.