The AI Engineer Course: Complete AI Engineer Bootcamp

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The AI Engineer Course: Complete AI Engineer Bootcamp

Published 8/2024
Duration: 16h52m | Video: .MP4, 1920x1080 30 fps | Audio: AAC, 44.1 kHz, 2ch | Size: 9.09 GB
Genre: eLearning | Language: English

Complete AI Engineer Training: Python, NLP, Transformers, LLMs, LangChain, Hugging Face, APIs

What you'll learn
The course provides the entire toolbox you need to become an AI Engineer
Understand key Artificial Intelligence concepts and build a solid foundation
Start coding in Python and learn how to use it for NLP and AI
Impress interviewers by showing an understanding of the AI field
Apply your skills to real-life business cases
Harness the power of Large Language Models
Leverage LangChain for seamless development of AI-driven applications by chaining interoperable components
Become familiar with Hugging Face and the AI tools it offers
Use APIs and connect to powerful foundation models
Requirements
No prior experience is required. We will start from the very basics
You'll need to install Anaconda. We will show you how to do that step by step
Description
The Problem
AI Engineer is best suited to thrive in the age of AI. It helps businesses take advantage of Generative AI by building AI-driven applications on top of their existing websites, apps, and databases. Therefore, it comes as no surprise that the demand for AI Engineers has been surging in the job marketplace.
However, supply has been very limited. It is difficult to acquire the skills necessary to be hired as an AI Engineer.
And how can you do that?
Universities have been slow at creating specialized programs that teach practical AI Engineering skills. (not to mention that the few attempts that exist are very expensive and time consuming)
Most online courses teach ChatGPT hacks and standalone technical skills, but it is difficult to understand how these skills fit in the complete picture.
The Solution
AI Engineering is a multidisciplinary field. It encompasses a wide range of topics.
Understanding of the AI field and how AI works in practice
Python programming
Natural Language Processing in Python
Large Language Models and Transformers
Building applications with orchestration tools such as LangChain
Vector databases with PineCone
Building AI-driven apps in practice
Each of these topics builds on the previous ones. And you risk getting lost along the way if you don't acquire these skills in the right order. For example, one would struggle in the practical application of Large Language Models before understanding how to work with Langchain. Or, it can be overwhelming to study Natural Language Processing before learning how to code in Python.
So, in an effort to create the most effective, time-efficient, and structured AI engineering training available online, we created The AI Engineer Bootcamp 2024.
We believe this is the first training program that solves the biggest challenge to entering the AI Engineering field
- having all the necessary resources in one place.
Moreover, our focus is to teach topics that flow smoothly and complement each other. The course teaches you everything you need to know to become an AI Engineer at a fraction of the cost of traditional programs (not to mention the amount of time you will save).
The Skills
1. Intro to Artificial Intelligence
Structured and unstructured data, supervised and unsupervised machine learning, Generative AI and foundational AI models. We know these buzzwords belong to the field of AI but what do they all mean?
Why learn it?
Gain a high-level understanding of the Artificial Intelligence field by going on a structured journey that will teach you what is AI, how important it is to have the right type of data to build AI models, which are the main types of techniques used to build AI, what is Generative AI and how AI researchers developed powerful foundational models such as GPT, Llama, Gemini, and Claude.
2. Python Programming
If you are serious about becoming an AI developer, you have to learn Python programming. No code tools are not going to be sufficient.
Python is a relatively new programming language and it is general-purpose. This means that you can use it to create web applications, computer games, and solve data science tasks. Python has a large ecosystem of libraries and tools, which make it particularly suitable for working with AI models.
Why learn it?
Python programming will become the key instrument you will use to talk to communicate to AI models and integrate their capabilities in your products.
3. Intro to NLP in Python
Get an introduction to Natural Language Processing (NLP). You will learn techniques that enable computers to understand, generate, and classify human language.
Why learn it?
NLP is the foundation on which state-of-the-art modern Generative AI models have been built. By taking this part of the program, you will gain the necessary skills to design and implement AI systems that can interact with human language in meaningful ways.
4. Introduction to Large Language Models
This part of the program will allow you to expand your Natural Language Processing capabilities by learning how to harness the amazing power of Large Language Models (LLMs). Get an introduction to important tools such as Transformers Architecture, GPT, Langchain, HuggingFace, BERT, and XLNet.
Why learn it?
This module is your gateway to understanding how Large Language Models work and how they can be applied to solve complex language-related tasks that require deep contextual understanding.
5. Building applications with LangChain
LangChain is a framework that allows for seamless development of AI-driven applications by chaining interoperable components.
Why learn it?
Learn how to create applications that can reason. LangChain facilitates the creation of systems where individual pieces, such as language models, databases, and reasoning algorithms, can be interconnected to enhance overall functionality.
6. Vector Databases
With emerging AI technologies, the importance of vectorization and vector databases is set to increase significantly. In this Vector Databases with Pinecone module, you'll have the opportunity to explore the Pinecone database-a leading vector database solution
.
Why learn it?
Learning about vector databases is crucial as it equips you with the ability to efficiently manage and query large volumes of high-dimensional data, which is typical in machine learning and AI applications. These technical skills would allow you to deploy performance-optimized AI-driven applications.
**What you get**
A $1250 AI Engineering training program
Active Q&A support
All the knowledge to get hired as an AI Engineer
A community of AI learners
A certificate of completion
Access to future updates
Solve real-life business cases that will get you the job
You will become an AI Engineer from scratch
We are happy to offer an unconditional 30-day money back in full guarantee. No risk for you. The content of the course is excellent, and this is a no-brainer for us, as we are certain you will love it.
Why wait? Every day is a missed opportunity.
Click the "Buy Now" button and become a part of our AI Engineer program today.
Who this course is for
You should take this course if you want to become an AI Engineer or if you want to learn about the field
This course is for you if you want a great career
The course is also ideal for beginners, as it starts from the fundamentals and gradually builds up your skills

Homepage:

https://www.udemy.com/course/the-ai-engineer-course-complete-ai-engineer-bootcamp/

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