Discovery & Motivation

When I first started thinking about switching careers, “data science” felt like a door to a room I wasn’t sure I could enter. I’d been working in operations in the UK for years , spreadsheets, scheduling, stakeholder calls   practical, satisfying work, but I kept feeling pulled toward solving problems with data. I wanted to build predictive models, work with real datasets, and make decisions driven by evidence. The problem? I had no formal coding background and I wasn’t sure how to make the leap.

That’s when I found Growthskale Education. A colleague mentioned Growthskale Education during a coffee break; another friend had taken a short analytics course and kept talking about the programme support and weekend classes. I spent an evening reading Growthskale’s learner stories and then the curriculum for IBSS University’s MBA in Data Science & AI that Growthskale Education facilitates. Everything about Growthskale Educationfelt different ,not just an online course, but a learner first pathway that promised mentorship, project-based learning, and career support. Growthskale Education wasn’t telling me to “learn Python and see you later”; Growthskale was offering a structured journey to actually become a data professional.

As a woman from the UK balancing part-time care responsibilities, the practicalities mattered: weekend classes, flexible mentoring hours, and a community I could lean on. Growthskale’s emphasis on live projects and dissertation support convinced me it would be the bridge from my non-tech operations role to a real data role. I applied because Growthskale made the transition feel achievable not a leap of faith, but a guided climb with steady footholds.

Enrollment & Onboarding

The enrollment experience was the first time I truly appreciated how Growthskale operates differently. The application process for IBSS University’s MBA in Data Science & AI (facilitated by Growthskale) was clear and supportive. Growthskale assigned me an admissions advisor who explained entry requirements, walked me through documentation, and importantly talked about career goals, not just grades. That conversation mattered: Growthskale asked what kind of role I wanted after the MBA and noted the skills gaps I’d need to fill to reach “Junior Data Scientist.”

Onboarding with Growthskale felt like joining a focused, friendly cohort. The first week was an induction run by Growthskale and IBSS University faculty together: introductions, an overview of the MBA structure, and practical sessions on how assessments and live projects would run. Growthskale’s induction included a short diagnostic to assess my maths and coding baseline; instead of making me feel exposed, Growthskale turned the results into a customised “bridge plan”  a set of micro-lessons and bootcamp sessions to catch me up on Python basics, statistics fundamentals, and essential SQL.Growthskale’s onboarding also matched me with a mentor  a working data science professional who understood the challenges of shifting careers midlife. My mentor met me weekly for the first two months to set learning goals, recommend resources, and offer reassurance. Growthskale arranged weekend classes for the module lectures (perfect for my work schedule), weekday live doubt sessions for problem areas, and small-group labs so I could practice coding with peers. The practicalities were immense: Growthskale’s learning platform held all lecture recordings, reading lists, lab notebooks, and a dedicated channel for doubt sessions where faculty and Growthskale mentors answered questions within 24 hours.

One practical thing that made a big difference: Growthskale’s structured portfolio checklist. From week one, Growthskale asked me to save my notebooks, document mini-projects, and upload reflections — so that by the time we reached the live project modules, I already had materials to build a job-ready portfolio. Growthskale also scheduled periodic career clinics — resume reviews, LinkedIn optimization, and mock interviews — in partnership with IBSS University’s careers team, all tailored to help someone — like me — transition from operations into data.

Classes & Learning Experience

When my weekend classes officially began with Growthskale and IBSS University, I felt both nervous and excited. Nervous because I had never coded before, and excited because this was the first structured step toward my dream career. Growthskale’s Learning Management System (LMS) quickly became my academic home. Everything I needed  lecture slides, recorded sessions, lab assignments, project briefs, and discussion forums  was neatly organized there. The LMS also tracked my progress, which gave me a sense of achievement every time I completed a module.The program was structured in a way that gently eased me into the world of data science. Growthskale faculty understood that many learners, especially career changers like me, came from non-technical backgrounds. We started with Python from the absolute basics: data types, loops, and functions. Our faculty spent weekends breaking concepts into digestible lessons, supplemented by Growthskale’s weekday doubt-clearing sessions where we could revisit any tricky parts. The teaching style was patient yet rigorous  no question felt too small to ask.

Once we were comfortable with Python basics, Growthskale gradually raised the bar. We progressed into more advanced concepts: object-oriented programming, data structures, and eventually machine learning algorithms. Growthskale made sure that every jump in complexity was accompanied by labs and small projects so we could apply what we were learning.

Parallel to Python, we began exploring other essential tools for data professionals. Growthskale’s curriculum introduced us to SQL for database management, Tableau and Power BI for data visualization, and advanced Excel analytics for quick business reporting. What made the classes unique was the hands-on approach: instead of passively listening, we were actively working on case studies. For example, we built dashboards in Power BI to visualize retail sales trends, wrote SQL queries to analyze customer purchase behavior, and created Python scripts to clean messy datasets.I particularly enjoyed the data visualization modules. Growthskale faculty emphasized that data storytelling is as important as data processing. I learned how to transform raw numbers into meaningful visuals that could drive decisions. For one project, I designed a Tableau dashboard to show customer churn trends, which later became part of my professional portfolio.

The weekend classes were more than lectures; they were collaborative labs. Growthskale encouraged peer-to-peer learning, grouping us into teams to solve problems together. Working with learners from diverse backgrounds — finance, operations, marketing, and IT — gave me different perspectives on data challenges. Faculty acted less like traditional teachers and more like mentors, guiding us through problem-solving while encouraging independence.Every weekend felt like a mini bootcamp. Growthskale kept the sessions interactive with quizzes, real-world datasets, and industry examples. And because everything was recorded and uploaded to the LMS, I could revisit lessons anytime during the week. That flexibility was invaluable, especially when balancing coursework with my job.

Looking back, these classes were the foundation of my transition. Growthskale didn’t just teach tools Growthskale gave me confidence. By starting with basics and layering knowledge step by step, Growthskale built a pathway from “someone with zero coding background” to “someone building predictive models and dashboards.” The classes weren’t easy, but with the structure and support, they became achievable.

Projects & Research Topics

One of the biggest strengths of the Growthskale and IBSS University MBA in Data Science & AI was its emphasis on hands-on projects. Growthskale didn’t just teach concepts in theory; every module came with an applied assignment that simulated real-world business challenges. For me, these projects were the turning point. They gave me tangible proof — to myself and eventually to employers — that I could move beyond operations and actually solve problems with data.

Project 1: Python Data Cleaning & E-Commerce Sales Analysis

Our very first project was deceptively simple: working with a raw CSV file of e-commerce transactions. The dataset had missing values, duplicate entries, and formatting errors. Using Python (Pandas and NumPy), I learned to clean, preprocess, and summarize data. Growthskale faculty guided us in writing scripts to calculate total sales, identify top-performing products, and segment customers. For someone from a non-tech background, seeing my first Python program generate real business insights was exhilarating.

Project 2: SQL for Customer Behavior Insights

Next, we moved to SQL-based projects. Growthskale provided a database simulating customer orders for a retail chain. I built queries to identify repeat buyers, calculate revenue by region, and analyze seasonal purchasing patterns. Growthskale encouraged us to approach these tasks as if we were data analysts advising management. This project showed me how database queries could directly support business strategy — a skill I later highlighted in my CV.

Project 3: Data Visualization with Tableau & Power BI

Visualization was a highlight of the program. Growthskale assigned us a project to design dashboards for a fictional telecom company analyzing customer churn. Using Tableau and Power BI, I built interactive charts tracking churn rate by age, region, and contract type. Growthskale faculty stressed not only technical accuracy but also storytelling: “How would you explain this dashboard to a CEO?” That lesson stayed with me. My final dashboard became a key piece of my job portfolio and was praised in interviews.

Project 4: Predictive Analytics for Credit Risk

As we advanced, the projects became more complex. One milestone was applying machine learning in Python to predict credit risk. We used logistic regression and decision trees on a dataset of loan applicants, training models to classify customers as low or high risk. Growthskale’s faculty guided us step by step, from splitting data into training and testing sets to interpreting accuracy scores. This project was eye-opening because it showed me how data science is applied in banking and finance — industries I had never worked in before.

Project 5: Natural Language Processing (NLP) for Customer Reviews

Another fascinating project was in Natural Language Processing (NLP). Growthskale gave us a dataset of product reviews and guided us in building a sentiment analysis model. Using Python libraries like NLTK and Scikit-learn, I learned how to tokenize text, remove stopwords, and classify reviews as positive or negative. This project introduced me to the world of unstructured data and how businesses use AI to listen to customer voices.

Project 6: Capstone Project — AI in Healthcare Resource Optimization

The highlight of the MBA program was the Capstone Project. Working in a small team, I researched how AI could optimize hospital resource allocation. Growthskale supported us with faculty mentors, datasets, and research templates. My role focused on building a predictive model to forecast patient admission rates based on historical data and seasonal patterns. We combined Python modeling with Power BI dashboards to present findings. This project became the foundation of my MBA dissertation, where Growthskale provided extended research support and one-on-one guidance for literature review, methodology design, and final defense preparation.

Dissertation & Research Support

If the projects gave me confidence, the dissertation gave me identity. It was the point in the Growthskale and IBSS University MBA in Data Science & AI where I stopped just “learning data science” and started being a data scientist. For many of us, the dissertation was intimidating at first. Research, academic writing, and rigorous analysis felt like a huge leap from weekend classes. But Growthskale made it structured, supported, and achievable.

Choosing the Right Topic

Growthskale organized a dissertation orientation workshop where faculty and industry mentors walked us through potential research directions. I still remember the Growthskale mentor asking: “What kind of problem excites you enough to spend six months with it?” That shifted my mindset — it wasn’t about picking a “safe” topic but about selecting one that aligned with both my curiosity and career goals.With guidance, I chose to focus my dissertation on:
“Predictive Analytics for Healthcare Resource Optimization: Using Machine Learning to Forecast Hospital Admission Rates.”

This tied directly to the capstone project I had enjoyed earlier and gave me a chance to apply my skills to a socially meaningful challenge. Growthskale faculty approved the proposal, then matched me with a dissertation supervisor who had expertise in applied machine learning.

Structured Guidance from Growthskale

Unlike many universities where learners are left to “figure it out,” Growthskale provided a clear roadmap:

1. Proposal Stage – Drafting a clear research question and methodology plan. Growthskale held weekly clinics where supervisors reviewed early ideas.
2. Literature Review – Growthskale shared academic resources, journal access, and templates for writing structured reviews. I learned how to evaluate prior research and identify gaps.
3. Data Collection & Preparation – Growthskale provided anonymized hospital datasets and also taught ethical guidelines on working with healthcare data.
4. Model Building – Weekly technical sessions helped me implement models in Python (time-series forecasting, regression, and random forest).
5. Analysis & Findings – Growthskale mentors gave feedback on presenting results in charts and tables, ensuring the dissertation was both academically sound and business-relevant.
6. Writing & Editing – Growthskale provided editing support, helping me polish the academic tone and meet formatting standards.
7. Final Defense Preparation – Before my viva, Growthskale arranged mock presentations. Faculty played the role of examiners, asking tough questions, which prepared me to answer with confidence.

The Research Experience

Working on the dissertation was like having one foot in academia and one in industry. I wasn’t just coding models; I was learning to justify why a method worked, how to interpret results, and how to translate findings into actionable insights. Growthskale supervisors taught me to bridge technical depth with practical application — a skill that employers later valued in interviews.

The most rewarding moment came when my model successfully predicted patient admission spikes during winter flu season with impressive accuracy. I presented my findings not only as charts but as a Power BI dashboard that visualized resource demand forecasts. Growthskale faculty praised my ability to combine statistical rigor with a clear narrative, and my dissertation was graded with distinction.

Beyond the Dissertation: Growthskale’s Mentorship

What impressed me most was that Growthskale didn’t treat the dissertation as a solitary task. Instead, it became a mentored journey. Growthskale supervisors checked in regularly, gave constructive feedback, and celebrated milestones. They encouraged me to aim for publication, suggesting I adapt my dissertation into a conference paper — something I would never have thought possible before joining Growthskale.

For me, the dissertation wasn’t just an academic requirement. It was proof — to myself and to future employers — that I could take a real-world business problem, design a rigorous methodology, and deliver meaningful insights with data science. And it was Growthskale’s structured, learner-first approach that made that transformation possible.

Career Guidance & Support

While the classes and dissertation gave me the technical knowledge I needed, it was the career guidance from Growthskale that turned those skills into a real job opportunity. Growthskale never treated career services as an “afterthought.” From the very beginning of the MBA in Data Science & AI with IBSS University, they integrated career planning into the learning journey.

Resume & Portfolio Building

Growthskale’s career mentors worked with me to redesign my CV from an operations profile into a data-focused one. They helped me highlight transferable skills — problem-solving, process optimization, stakeholder management — and blend them with the new technical competencies I had gained (Python, SQL, Tableau, Machine Learning). Growthskale also guided me in creating a professional GitHub portfolio where I showcased my projects: dashboards, predictive models, and NLP scripts. Having this digital portfolio made me stand out in interviews.

Mock Interviews & Career Clinics

Every few weeks, Growthskale organized career clinics where industry mentors simulated real interview scenarios. I was asked questions about Python coding, SQL queries, and even business case studies on how data could reduce costs or increase customer satisfaction. The feedback was immediate and constructive, helping me refine both my technical answers and my communication style. Growthskale also provided behavioral interview training, teaching me how to frame my career transition story with confidence.

Job Search Strategy

Another area where Growthskale shone was in job search support. They provided targeted job boards, helped me filter roles that suited “career changers” rather than only experienced data scientists, and taught me how to network effectively on LinkedIn. Growthskale even arranged exclusive recruitment drives with partner companies where learners like me got early access to openings.

One-on-One Mentorship

Perhaps the most valuable part of Growthskale’s career support was the one-on-one mentorship. My assigned career mentor, a practicing Data Scientist in London, met with me virtually every month. She guided me on choosing the right job roles, reviewed my application strategies, and shared insights into what hiring managers look for in junior-level candidates. Having someone who had walked the path before made the journey feel less daunting.

Transitioning into My Role

With Growthskale’s support, I applied confidently and secured my first role as a Junior Data Scientist at Mitiga Solution . In the interview, I showcased my Power BI dashboards, explained my credit risk model, and even discussed insights from my dissertation research. The employer was impressed not just by the technical skills but by the structured learning journey I had taken — and I owe that presentation readiness to Growthskale’s career guidance.