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- Overview
Educational accomplishments and income are closely correlated. Education and skill with endorsed certificates from credible and renowned authorities typically lead to better jobs with attractive salaries. Educated and skilled workers also have lower rates of unemployment. Therefore, skills and endorsed certificates to showcase are essential for people early in their careers.
- Why Choose Imperial Academy?
Imperial Academy offers this premium LangChain in Action: Develop LLM-Powered Applications course to ensure security in your career. In addition, this comprehensive LangChain in Action: Develop LLM-Powered Applications course will assist you in building relevant skills that will help you find a job in the related sectors. Also, the Certificate you’ll get after completing the LangChain in Action: Develop LLM-Powered Applications will put your head and shoulder above others in front of potential employers.
Become the person who would attract the results you seek. What you plant now, you will harvest later. So, grab this opportunity and start learning LangChain in Action: Develop LLM-Powered Applications!
- What Imperial Academy Offers You
- QLS/ CPD/ CIQ Accredited
- 24/7 Assistance from our Support Team
- 100% Online
- Self-paced course
- Bite-sized Audio-visual Modules
- Rich Learning Materials
- Developed by Industry Specialists
- Career Guidance
- Course Design
Learn at your own pace from the comfort of your home, as the rich learning materials of this premium course is accessible from any place at any time. The advanced course curriculums are divided into tiny bite-sized audio-visual modules by industry specialists with years of experience behind them.
- Audio-visual Lessons
- Online Study Materials
Course Curriculum
| Before we start | |||
| Why this course is different | 00:01:00 | ||
| Prerequisites | 00:01:00 | ||
| Essential topics and terms (theory) | 00:04:00 | ||
| Why this course does not cover Open Source models like LLama2 | 00:01:00 | ||
| Optional: Install Visual Studio Code | 00:02:00 | ||
| Get the source files with Git from Github | 00:02:00 | ||
| Create OpenAI Account and create API Key | 00:02:00 | ||
| Preparation | |||
| Setup of a virtual environment | 00:03:00 | ||
| Setup OpenAI Api-Key as environment variable | 00:03:00 | ||
| Exploring the vanilla OpenAI package | 00:03:00 | ||
| LangChain Basics | |||
| LLM Basics | 00:07:00 | ||
| Prompting Basics | 00:02:00 | ||
| Theory: Prompt Engineering Basics | 00:02:00 | ||
| Few Shot Prompting | 00:05:00 | ||
| Chain of thought prompting | 00:02:00 | ||
| Pipeline-Prompts | 00:04:00 | ||
| Prompt Serialisation | 00:03:00 | ||
| Chains - From basic to advanced chains | |||
| Introduction to chains | 00:01:00 | ||
| Basic chains – the LLMChain | 00:03:00 | ||
| Response Schemas and OutputParsers | 00:06:00 | ||
| LLMChain with multiple inputs | 00:02:00 | ||
| SequentialChains | 00:04:00 | ||
| RouterChains | 00:04:00 | ||
| Callbacks | |||
| Callbacks | 00:05:00 | ||
| Memory | |||
| Memory basics – ConversationBufferMemory | 00:04:00 | ||
| Conversation Summary Memory | 00:03:00 | ||
| EXERCISE: Use Memory to build a streamlit Chatbot | 00:01:00 | ||
| SOLUTION: Chatbot with Streamlit | 00:03:00 | ||
| OpenAI Function Calling | |||
| OpenAI Function Calling – Vanilla OpenAI Package | 00:08:00 | ||
| Function Calling with LangChain | 00:04:00 | ||
| Limits and issues of the langchain Implementation | 00:03:00 | ||
| Retrieval Augmented Generation (RAG) | |||
| RAG – Theory and building blocks | 00:03:00 | ||
| Loaders and Splitters | 00:04:00 | ||
| Embeddings – Theory and practice | 00:04:00 | ||
| VectorStores and Retrievers | 00:07:00 | ||
| RAG Service with FastAPI | 00:05:00 | ||
| Agents | |||
| Agents Basics – LLMs learn to use tools | 00:06:00 | ||
| Agents with a custom RAG-Tool | 00:08:00 | ||
| ChatAgents | 00:03:00 | ||
| Indexing API | |||
| Indexing API – keep your documents in sync | 00:02:00 | ||
| PREREQUISITE: Docker Installation | 00:01:00 | ||
| Setup of PgVector and RecordManager | 00:04:00 | ||
| Indexing Documents in practice | 00:06:00 | ||
| Document Retrieval with PgVector | 00:03:00 | ||
| LangSmith | |||
| Introduction to LangSmith (User Interface and Hub) | 00:02:00 | ||
| LangSmith Projects | 00:07:00 | ||
| LangSmith Datasets and Evaluation | 00:13:00 | ||
| Microservice Architecture for LLM Applications | |||
| Introduction to Microservice Architecture | 00:04:00 | ||
| How our Chatbot works in a Microservice Architecture | 00:02:00 | ||
| Introduction to Docker | 00:05:00 | ||
| Introduction to Kubernetes | 00:02:00 | ||
| Deployment of the LLM Microservices to Kubernetes | 00:13:00 | ||
| LangChain Expression Language (LCEL) | |||
| Intro to LangChain Expression Language | 00:01:00 | ||
| LCEL Part 1 – Pipes and OpenAI Function Calling | 00:07:00 | ||
| LCEL – Part 2 – VectorStores, ItemGetter, Tools | 00:06:00 | ||
| LCEL – Part 3 – Arbitrary Functions, Runnable Interface, Fallbacks | 00:07:00 | ||
Certificate of Achievement
Learners will get an certificate of achievement directly at their doorstep after successfully completing the course!
It should also be noted that international students must pay £10 for shipping cost.
CPD Accredited Certification
Upon successfully completing the course, you will be qualified for CPD Accredited Certificate. Certification is available –
- PDF Certificate £7.99
- Hard Copy Certificate £14.99
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