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Emmanuel
- Rate RM214
- Response 17h
-
Students2
Number of students accompanied by Emmanuel since their arrival at Superprof
Number of students accompanied by Emmanuel since their arrival at Superprof

RM214/h
1st lesson belanja
- Data Analysis
A data and AI professional with over 10 years experience in the industry
- Data Analysis
Lesson location
About Emmanuel
I’m Dr. Emmanuel Ogungbemi—a data scientist, engineer, and educator with over a decade of hands-on experience in analytics, machine learning, and data engineering. After earning my PhD in Engineering & Computing, I’ve worked across government (Ofgem), aviation (NATS), energy (BP), consultancy (BIP, Multiverse), and academia (University of the West of Scotland), helping teams build scalable data platforms, craft predictive models, and deploy AI solutions in production. Today, I split my time between leading data‐driven projects in the UK Civil Service and tutoring data science, machine learning, and programming to university students and early-career professionals.
My teaching philosophy is simple: I believe that strong conceptual foundations—paired with real-world, hands-on coding—are the key to becoming confident in data science. Whether you’re just starting out with Python and pandas or you’re already wrestling with TensorFlow, scikit-learn models, and deep-learning frameworks, I’ll meet you at your level and guide you step by step:
Conceptual Clarity: We’ll work through the core building blocks of ML (data preprocessing, feature engineering, model selection, evaluation metrics) using clear, jargon-free explanations.
Live Coding & Feedback: Lessons happen via webcam (Zoom/Skype), where I share my screen and walk you through Jupyter notebooks or your preferred IDE. You’ll code alongside me, and I’ll provide instant feedback—so you truly understand why each line of code exists and how to debug common pitfalls.
Project-Driven Learning: Rather than generic “examples,” I tailor every exercise to your specific goals: building classification models, natural language processing pipelines, or full data-engineering workflows. By the end of each session, you’ll have working code that directly feeds into your university project or portfolio.
Ongoing Support: Between lessons, I share reading materials, mini-assignments, and reference notebooks. As you work on your data science project, I review your progress, suggest optimizations (like hyperparameter tuning or pipeline refactoring), and help you interpret results for your final report or presentation.
What You’ll Gain from My Sessions
A solid grasp of core libraries (Python, pandas, NumPy), plus hands-on experience with scikit-learn, TensorFlow/PyTorch, and Azure/AWS data tools.
The confidence to architect end-to-end machine learning pipelines, from raw data ingestion and cleaning through to model deployment and evaluation.
Practical insights into best practices for reproducible research: version control (Git), notebook organization, and code testing.
Tips for writing clear, impactful technical reports—so your supervisors and peers can follow your methodology and results.
Why Choose Me on Superprof?
Industry & Academic Expertise: With roles ranging from leading Ofgem’s Common Data Platform (boosting data accessibility by 30%) to designing a 99.4%-accurate NLP classifier for BP, I bring both academic rigor and real-world problem-solving to the table.
Customized Curriculum: We’ll start by assessing your current skillset and project requirements, then build a lesson plan that targets exactly what you need—for instance, tackling a classification case study with scikit-learn or implementing a deep-learning model on Azure Databricks.
Flexible Scheduling: I offer weekday evening slots (5pm–8pm London time) and can accommodate intense, accelerated schedules if your deadline is approaching.
Student Success: Past learners have gone on to publish conference papers, secure top grades on final year projects, and land graduate roles at leading tech firms—all thanks to the hands-on guidance and structured learning path we used together.
If you’re passionate about leveling up your data science skills and want to complete your university project with confidence, let’s connect. Click “Contact” to send me a message, and we can arrange a free 30-minute introductory session. In that call, we’ll discuss your dataset, outline your project goals, and I’ll give you a short coding demo so you can see my teaching style in action. I look forward to helping you master machine learning and achieve stellar results.
See you soon,
Dr. Emmanuel Ogungbemi
About the lesson
- Primary
- Secondary
- SPM
- +12
levels :
Primary
Secondary
SPM
Form 6
STPM
Adult education
Bachelor
Masters
Diploma
Doctorate
Beginner
Intermediate
Advanced
Professional
Kids
- English
All languages in which the lesson is available :
English
I cover SQL, python, pyspark, power bi, data science, data engineering and machine learning.
Lesson Structure & Format
Live, Interactive Sessions (via Webcam):
We’ll meet over Zoom (or your preferred video platform) in real time. I share my screen to walk you through code––and you code alongside me. This ensures you see both the “why” and the “how” of every step in Python, Jupyter notebooks, or your chosen IDE.
Typical Duration:
Each lesson is 90 minutes by default. This gives us enough time for:
A brief recap of the previous session (10 min)
Core concepts & hands-on coding (60 min)
Q&A and next-steps discussion (20 min)
If you prefer 60-minute or 120-minute blocks, just let me know—schedules are flexible.
Hands-On, Project-Driven Focus:
At the start of our first lesson, we’ll review your dataset and project objectives. From lesson 2 onward, every coding example, exercise, and discussion is directly tied to building or improving your actual data science project. By the time you finish, you’ll have a working pipeline that you can present or submit.
Rates
Rate
- RM214
Pack rates
- 5h: RM907
- 10h: RM1601
online
- RM214/h
free lessons
This first lesson is free to allow you to get to know your teacher so that they can best meet your needs.
- 1hr
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