Meet Ashwini: the Trainer Making AI Accessible to All

Meet our AI trainer Ashwini and learn about our courses and how people from all walks of life are benefiting from them. Ashwini is a former software developer by background but found her calling through teaching, which gives her a genuine connection with learners. Ashwini helps develop our educational content and feels inspired when our learners go on to fulfil their ambitions after completing their courses.

Who is the Typical Learner on an AI Course?

It varies. In the current cohort there is no one from a tech background. Learners come from sales, marketing, HR, health coaching, nursing, and similar fields. Previous cohorts have included people with data or software backgrounds, but they are the exception. Most learners are in their 30s and 40s, though we have had learners in their 50s too. One was 54 and went on to build her own AI tool and launch an AI consultancy, which was genuinely inspiring.

What is the Biggest Misconception People Have About AI Training Before They Start?

That ChatGPT will do everything for them in one click. When they arrive they expect to simply type a question and have the AI produce a finished product. The reality is that ChatGPT is an assistant and will guide and support you, but you still have to do the work: setting up your environment, organising your project files, and connecting different components. For some learners, the hands-on requirement can be more than anticipated, but it is a great way to learn.

Are Learners Expected to Write Code?

We do not teach deep coding. The course uses pre-written scripts, and I spend roughly two to three days introducing learners to the structure and logic of programming. Python reads almost like English, so most learners start to follow it without needing to memorise syntax. We use AI tools such as ChatGPT and Copilot to generate code, and the skill we are building is knowing how to use and adapt that output rather than write everything from scratch. That said, learners who want to go line by line through the code can book a Friday one-to-one with me, and quite a few do.

What Does the Learning Journey Look Like Week by Week?

Teaching runs Monday to Thursday, 6pm to 9pm, online via Microsoft Teams. Every session has a 50-minute teaching block, then a 10-minute break, so there are two breaks across the three hours. The first six weeks build foundations: what programming is, why it matters, and the core concepts of machine learning and deep learning. From week seven, the pace picks up and learners begin connecting theory to practical work. The final piece is the capstone project, where every learner builds something that solves a real business problem. Friday is reserved for one-to-one support.

Which Part of the Curriculum Generates the Most Eureka Moments?

Without question, the capstone project. This is where everything comes together. Learners move from understanding concepts to actually building real, working tools that solve real business problems across areas like sales, health, and customer service. The moment they see their solution working in front of them, their confidence grows instantly. That’s when everything truly clicks.

What Real-World Skills Do Learners Walk Away With?

A working knowledge of Python for data tasks, an understanding of machine learning and deep learning algorithms, practical experience with a range of current AI tools, and an appreciation of AI ethics in business decision-making. Those who want to move into technical roles are well placed to apply for junior AI engineer, junior Python developer, or junior data scientist positions. Those who want to stay in their existing field can apply what they have learned to make their day-to-day work more efficient and data-informed.

How Do You Measure Whether a Learner Has Truly Understood the Material?

We use the engagement platform Nearpod for in-session assessment. After every 50-minute block, I run an activity such as an open-ended question, a poll, a fill-in-the-blanks exercise, or sometimes an audio recording where learners explain a concept back in their own words. Every Friday, learners receive a personalised report generated by iMeta’s own feedback tool. It draws together their quiz scores, attendance, and activity results, and the AI then produces individual commentary: what they did well, where they fell short, and what to focus on next.

Do Learners Go On to Use AI and Python in Their Roles After Training?

I can point to many learners who are actively using what they learned. In the current cohort it is too early to say, but several are already looking for new roles and some have had interviews. What is clear is that not everyone moves into a technical job, and that is fine: the course still delivers real value for people who want to improve their current role or start something of their own.

Can Learners Who Do Not Move Into Technical Roles Still Get Value From the Course?

Absolutely. Some of our most compelling success stories involve learners who have used the course to build businesses rather than get jobs. One health coach who had been working in a traditional practice built an AI-powered platform and now has more than 100 clients enrolled through it. Another learner started a software development firm taking AI projects from clients worldwide. Another launched an AI consultancy helping other businesses adopt the technology. The course gives people the tools to create something, and for many that is more valuable than a job title change.

What Makes iMeta’s Teaching Approach Different From Other Online AI Courses?

A few things set iMeta apart. Our approach is highly structured and learner-focused. Every learner receives a weekly personalised feedback report, participates in interactive sessions every day, and has access to a dedicated one-to-one support session each Friday. Beyond teaching, we provide a full careers and employment service, including CV building from scratch, interview preparation, and continued support for six months after the course.

We also place strong emphasis on inclusivity, with dedicated support for learners with additional needs. Most importantly, our curriculum is flexible and responsive. If learners want to explore a topic like prompt engineering, we adapt quickly and bring it into the learning journey. This creates a course that is not only structured, but also personalised and relevant.

How Do You Keep Learners Engaged Across Evening Online Sessions?

It requires constant effort! Most learners are coming straight from a full working day. I do not force cameras on, but I find that once I explain why it matters, that I am teaching people, not screens, almost everyone switches their camera on themselves. I break up every session with discussion: I stop, ask for opinions, and make space for learners to share their own experiences with the topic. On top of that, every week includes a 30-minute personal and professional development lesson, such as communication skills and community engagement, which tends to generate a lot of positive conversation.

What Support Do Learners Need Beyond the Classroom to Succeed?

Some learners find the pace a little challenging: a new concept, a new algorithm, or a new tool every day for thirteen weeks. I make sure supplementary study materials are available for anyone who needs to consolidate between sessions. Beyond that, the employment support team is central. They help learners prepare CVs from scratch, coach them through interviews at short notice, and stay in contact for six months after the course ends. That ongoing relationship is something I think genuinely sets iMeta apart.

What is the Most Important Thing to Communicate to Potential Learners in the West Midlands?

That this course is built for people with no tech background. The main aim is to make learners more productive, more data-literate, and better prepared for an AI-enabled workplace. That applies in every industry, whether someone wants to move into a technical role, grow their own business, or simply do their current job more effectively.

As an AI Trainer, What is Your View on the Future of Work?

I am an optimist. Roles built around repetitive, manual tasks such as data entry, basic reporting, or routine scheduling are already being automated, and that will accelerate. But AI is simultaneously creating new roles that did not exist five years ago: prompt engineering is an obvious example, and there are many others. The areas that will grow are those requiring human judgement, creativity, relationship building, and ethical reasoning. Within five years I think AI fluency will be a baseline expectation in most professional roles, just as digital literacy is today.

For the West Midlands, the opportunity is significant. Public sector organisations, local authorities, and NHS bodies are already exploring AI to reduce administrative workload, improve compliance, and enhance service delivery. If that adoption is done well, with people who understand how the tools work and how to apply them responsibly, the productivity gains could be substantial.

Finally, if You Had to Describe Our AI Training in One Sentence, What Would You Say?

It is a practical, hands-on programme that turns beginners into confident AI users who can apply data and automation to everyday business problems, regardless of their technical background.

Thanks Ashwini! To find out more about our courses, get in touch via info@imetatraining.co.uk