How to Transition into AI/ML

5 actionable steps to follow

Author

Himanshu Ramchandani
July 27, 2024 • Estimated Reading Time: 6 minutes

8 Days to Close → GenerativeAI Live Bootcamp

In today’s edition, I will share actionable steps to transition into AI.

You have years of experience in your industry and probably heard of AI on social media and among your colleagues.

You had thought about learning it and searched on the internet on How to?

I will share the “How-to” guide with you so that you can also create opportunities in your career.

Let’s dive in.

I get this question a lot "How to switch to AI if I am from a tech or non-tech background?”

If you have the same question, You probably have this picture in mind →

  • you are the go-to expert for AI in your team

  • you are the authority in the AI space

  • you understand the tech jargon

Data is the fuel to all AI systems.

AI/ML is a technology that can be integrated into any sector since all sectors have data.

You do not need to start from zero even if you have years of experience.

How?

Himanshu Ramchandani

Let me show you the path.

You can customize it according to your needs.

Here are 5 actionable steps to follow for all experienced professionals.

1 → Current knowledge + AI

If you have n years of experience in any field you do not need to start from 0 in AI/ML, as this field can be applied in any sector.

If you drop your previous field, the experience becomes zero and now you are a fresher.

You don't want that. Right?

Use your current knowledge and see how it can be integrated with Artificial Intelligence.

Example →

Let’s say you are working in the Finance sector, pick different datasets from finance, and start your analysis.

In AI/ML you need domain expertise and tech both to solve a problem better.

You are not a fresher, you already have soft skills and domain knowledge.

2 → Follow a Roadmap

AI/ML Roadmap

Pick any roadmap that you want and try to stick to it until you spend at least a month on it.

This will save you time and create a learning structure for you.

The topics that create gaps, you can fill those gaps by searching on the internet.

You can start with any topic you want, but if you know Machine learning you will better understand Deep Learning.

And if you know Deep Learning, you will better understand GenerativeAI.

All of these tech boom are just part of the process, you should focus only on learning and getting better.

Hard work beats Talent. Remember?

5 years ago I created this Roadmap, I kept on updating the topics.

Important ones were added, and irrelevant ones were removed.

Here is the AI/ML Roadmap

3 → Real-world Data

Gain experience working with real-world data.

This can include participating in online AI competitions, working on personal projects, or interning or volunteering with organizations.

The more you work with huge and complex datasets, the more you will understand the fuel that runs AI models.

You will find everything in the roadmap above.

If you are from the finance sector, work on the datasets from finance and solve different problems in the same sector.

This will make you an expert who has hybrid skills. (finance + data + AI)

Deadly combination.

Note: Only work on problems that are already in your domain of expertise.

4 → Proof Of Work

GitHub - hemansnation

Build a portfolio of your AI/ML projects and accomplishments.

This can include projects you've worked on, papers you've published, or presentations you've given on AI/ML topics.

Write blogs on how you built the project and what challenges you have overcome.

This will give you a sense of achievement and the recruiter a proof of work.

Any of the following can be considered as proof of work →

  • Research paper

  • Code on GitHub

  • Deployed on cloud

  • Presentations, Lectures and Talks

  • Blog that explained how you build it

  • Working demonstration of your project

5 → Community + Network

Network with other data professionals in the field.

You will be attending conferences and events, and joining online communities and forums, to connect with AI experts on LinkedIn.

Don't be afraid to ask for help or clarification when you need it.

Simple hack →

Don’t ask people to be your mentor. That will create pressure for them as so many people ask that.

Just ask whatever question you have, and they will be happy to respond.

Join the community →

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