Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
2 Hour(s) 1 Minute(s)
Language
English
Taught by
E SKILLIFY, Eng.Mariam Omar
Rating
3 views
Course Overview
API, ChatGPT, Prompt Engineering, Finetuning, OpenAI, Integrate ChatGPT, Business AI, Generative AI, Chat GPT 4
In this course, you will discover the power of GPT-3 in creating conversational AI solutions.
We will start with an introduction to chatbots and their use cases, and then dive deep into GPT-3 and its capabilities. You will learn how to fine-tune the model for specific tasks, such as customer service, lead generation, or entertainment. We will cover techniques for improving the accuracy and fluency of the chatbot's responses, as well as strategies for handling user input and managing conversation flow.
Next, we will explore different ways to integrate GPT-3 chatbots with various platforms and channels, such as messaging apps, voice assistants, and social media. You will learn how to use APIs and SDKs to connect your chatbot to these platforms and leverage their features, such as natural language processing, voice recognition, or rich media support. We will also cover best practices for designing chatbot user interfaces and testing and deploying your chatbot in production.
By the end of this course, you will have a solid understanding of how GPT-3 works and how to use it to build powerful and engaging chatbots for your business or personal projects. You will have hands-on experience with fine-tuning GPT-3 models and integrating them with various platforms and channels, and you will be ready to apply these skills in real-world scenarios.
Course Content
- 5 section(s)
- 22 lecture(s)
- Section 1 Introduction to Fine-Tuning
- Section 2 Formatting data for Fine-Tuning
- Section 3 Fine-Tuning a Model
- Section 4 Develop your own chatbot based on GPT 3.5 Model
- Section 5 Data Preparation, Fine-Tuning, and Testing of GPT-3.5 Turbo Models
What You’ll Learn
- Understand key concepts of fine-tuning pre-trained models.
- Learn to determine if fine-tuning is appropriate for a specific problem.
- Identify types of pre-trained models and their strengths and weaknesses.
- Prepare data for fine-tuning with tokenization and encoding.
- Fine-tune a pre-trained model for a specific NLP application
Skills covered in this course
Reviews
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SSreerajv
excellent course
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MManivannan Kannan
Very good, however reduce the speed while doing the explanation.
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PParuchuri Gopi
good exploration in AI knowledge
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CChandrakant Nazirkar
its awesome training
