What are the most In-Demand Skills in Generative AI?

What are the most In-Demand Skills in Generative AI?

What exactly to learn in Generative AI to get hired ๐Ÿ’ผ? (Including best courses and certifications links)


4 min read

Gen AI will create 3.7 million jobs by 2025, according to Gartner. But what should you learn in Generative AI? Here are the top 8 most demanded Generative AI skills you can learn in a short time (as a techie) ๐Ÿš€:

Customized LLMs:

These days, every organization wants LLMs to be trained on or used with their private data. For this, two skills are particularly hot๐Ÿ”ฅ:

1. RAG (Retrieval Augmentation Generation) - This technique involves fetching relevant information from your private database in response to user queries and providing it to the LLM. In short, you're chatting with your own data.

To know more: https://chat.openai.com/share/e68e42e5-75a0-440b-b10e-757407558792

2. Fine-Tuning LLM - This is like teaching a mini-course on a specific topic or style to a pretrained LLM, enhancing its ability to understand and generate responses related to a particular subject. In short, it's a style alignment process.

To know more: https://chat.openai.com/share/33fae8af-413e-43f6-9c99-9952abef2a7f

Virtual Agents:

The future lies in using LLMs to interact with other parts of your application, such as in your travel app, where you can command the LLM to perform actions like booking flights, extending hotel reservations, updating profiles, etc. This is done via things like Function calling (Function calling - OpenAI API) where you code LLMs to call specific functions in your code to perform specific actions.

To know more: https://chat.openai.com/share/0629cd62-db57-4676-9c3c-f53e2ac7a19f

Multimodal AI:

AI that can process multiple data inputs, such as both text and images. Users can input an image and ask questions about it, receiving an answer in text, or vice versa. For example, a fintech company wants to use an LLM with their financial reports, which consist of charts, figures, text, and tables, so using multimodal AI (like GPT + DALLยทE) would be highly useful here.

To know more: https://chat.openai.com/share/cb83863f-28c3-4293-af97-08f63b1b7eba

Open Source Models:

OS models are a low-cost solution that offers data privacy as a cherry on top. You can further improve it as per your needs. Thus, working knowledge of top OS LLM models like Mistral 7B, Meta LLaMA 2, DBRX and Google Gemma is an outstanding skill. Plus, understanding OS LLM architecture and building on top of it distinguishes you from others.

To know more: https://chat.openai.com/share/44abcc59-d9c7-4436-a5e4-24acad03f637

AI-Centric Cloud:

Developers with knowledge of cloud services like AWS Bedrock, Google Vertex AI, and Azure Cognitive Search are in high demand. These services allow organizations to easily use multiple foundational LLM models and perform other LLM operations like fine-tuning with just a few clicks. Knowing which specific cloud service efficiently solves a specific AI problem is a new wisdom.

To know more: https://chat.openai.com/share/d9724a3b-c957-4a26-9e20-da551681b4eb

Cost-Saving Optimization Techniques ๐Ÿ’ธโœ‚๏ธ:

LLM operations are costly to run like Finetuning an LLM can make a hole in your pocket as GPU prices are at the peak. So new optimized fine-tuning techniques like LoRA(low-rank adaption) are developed. LoRA lets you fine-tune the model to perform well on specific tasks or datasets without the heavy computational cost of full training. So, learn to optimize various LLM operations costs.

To know more: https://chat.openai.com/share/03246597-0800-47c9-9fa4-284b544622ea

Small Models:

You can't use GPT-4 for every task as once traffic rises up it will empty your funds. Thus, using lightweight small models for simple tasks is key to saving costs. Knowing various small models available on Hugging Face and which model to use for which problem is a rare skill.

To know more: https://chat.openai.com/share/9d8704ff-c7bb-4183-8b2a-cd19b854ea3b

AI Ethics & Regulation:

Many governments are becoming strict on AI development, issuing guidelines and, in some cases, legal actions, as seen with Gemini facing a lawsuit from the Indian government due to policy aversion. Thus knowledge of building responsible AI and following ethical guidelines as per the law is a must.

To know more: https://www.perplexity.ai/search/Tell-why-building-zED49wuxTzaQkzCJfMHVBQ

That's all for top skills. Now here's the gem๐Ÿ’Ž: ๐Ÿ‘‡

Direction is more important than speed โœ…. This article has given you the right direction to channel your efforts into the never-ending Generative AI market. To give you more leverage ๐Ÿ”‘, here are some of the best resources and certifications for Gen AI skills:

  1. LangChain for LLM Application Development - DeepLearning.AI

  2. LangChain: Chat with Your Data - DeepLearning.AI

  3. Free Generative AI Courses with certifications - Activeloop

  4. Databricks: Large Language Models: Application through Production | edX

  5. Generative AI with LLMs Certification | NVIDIA

  6. AI Engineering | Coursera

I post valuable knowledge ๐Ÿ“š regarding these skills every week ๐Ÿ—“๏ธ using real-life examples ๐ŸŒ. Connect if you have a Growth Mindset ๐ŸŒฑ.๐Ÿš€.

Donโ€™t forget to like ๐Ÿ‘, comment ๐Ÿ’ฌ, and share ๐Ÿ”„ the article, it will motivate me to spend more time in research ๐Ÿ› ๏ธ to give you the best content possible.