Hands On Introduction to Data Analytics with Power BI Practical Sessions for Real-World Insight

From 295 C$ /h

Power BI is one of the most powerful tools for turning raw data into meaningful insights.
In this class, you’ll learn how to connect data sources, clean and transform data, create interactive dashboards, and visualize insights that support smart business decisions.

Through practical, hands-on exercises, you’ll gain the skills to analyze trends, identify patterns, and communicate results effectively, whether you’re a student, business professional, or aspiring data analyst.

Extra information

Bring your own laptop with Power BI Desktop installed (free download from Microsoft Store).

Location

Online from United Kingdom

About Me

Hi, I’m Okechukwu, a passionate educator and technology professional with over six years of experience across Data Analytics, Quality Assurance, Cloud Computing, and Software Development. I’m currently pursuing a Master’s in Artificial Intelligence at the University of Wolverhampton, where I focus on data science, machine learning, and intelligent automation.

I love helping learners build both technical competence and confidence. Whether you’re a beginner looking to understand coding concepts, a student aiming to master mathematics and logical reasoning, or a professional seeking to break into the data or tech field, I design lessons that are interactive, practical, and goal-oriented.

Beyond tech, I’m also an avid chess player, teaching the game not only as a sport but as a tool for strategic thinking, focus, and patience. My students enjoy learning through real-world examples, structured progress tracking, and a supportive learning environment tailored to their needs.

Education

Master’s in Artificial Intelligence (Ongoing)
University of Wolverhampton, United Kingdom
2025 – Present
Focus: Data Science, Machine Learning, and Intelligent Automation

Diploma in Data Science
National Institute of Information Technology (NIIT), India
2020 – 2021

B.Eng (Hons) in Computer Engineering
Michael Okpara University of Agriculture, Nigeria
2012 – 2017

Experience / Qualifications

Experience

Solutions Consultant – Sonicom (Remote, Abuja)
May 2022 – Present

Designed and implemented AI-powered, cloud-integrated platforms to automate business workflows.

Delivered data-driven solutions improving efficiency and decision-making.

Mentored junior engineers and provided technical guidance to cross-functional teams.

Solutions Architect – Industrial Arbitration Panel (IAP)
Oct 2024 – Oct 2025

Developed secure and scalable IT systems to streamline arbitration processes.

Led architecture design and system analysis aligned with business and regulatory requirements.

Senior QA Engineer & DevOps Specialist – HNG Tech
Jun 2024 – Nov 2024

Built QA automation frameworks using Selenium and Postman, cutting manual testing by 60%.

Deployed CI/CD pipelines to enhance deployment speed and reliability.

Product Development Lead & QA Engineer – Havosoft International Ltd.
Sep 2023 – Oct 2024

Managed multiple software projects using Agile methodologies.

Increased platform adoption by 25% through innovative feature development.

Chief Technology Officer (CTO) – Dotmac Technology Ltd.
Aug 2022 – Jul 2023

Directed a team of engineers maintaining 2,000+ client networks.

Reduced network downtime by 35% through proactive system monitoring.

Chess Tutor (Freelance)
2018 – Present

Teach beginners and intermediate players the fundamentals and strategies of chess.

Focus on improving decision-making, focus, and strategic reasoning.

Conduct both in-person and online lessons.

Qualifications

AWS Certified Cloud Practitioner (2022) – Cloud architecture & deployment.

Certified Software Tester (CST, 2024) – Functional, regression & automation testing.

Power BI Certified Analyst (2024) – Data visualization & business intelligence reporting.

Prompt Engineering with ChatGPT (2024) – Applied prompt design for LLM workflows.

HNG Product Testing Certificate (2024) – Agile QA, test case design & automation.

Senior QA Engineer & DevOps Specialist – Micro1 (2025)

B.Eng in Computer Engineering – Michael Okpara University of Agriculture.

Diploma in Data Science – NIIT India.

Age

Children (7-12 years old)

Teenagers (13-17 years old)

Adults (18-64 years old)

Seniors (65+ years old)

Student level

Beginner

Intermediate

Advanced

Duration

90 minutes

The class is taught in

English

Skills

Computer science

Availability of a typical week

(GMT -05:00)

New York

Online via webcam

Mon

Tue

Wed

Thu

Fri

Sat

Sun

00-04

04-08

08-12

12-16

16-20

20-24

Master Chess for Beginners and Strategic Thinkers.

373 C$ /h

Chess is more than just a game, it’s a science of strategy, patience, and decision-making.
In this class, I’ll guide you through the fundamentals of chess, from understanding the board and piece movements to mastering tactics, openings, and endgame strategies.

You’ll also learn how to analyze your moves, recognize opponent patterns, and develop a logical approach that strengthens your focus and critical thinking.

Whether you’re a beginner eager to learn or an intermediate player aiming to sharpen your game, this class provides structured lessons, real-match practice, and personal feedback to help you grow into a confident player.

Khalil

4.9

(69)

If you’ve ever felt that science and math are difficult, it’s probably because no one showed you how to think like a problem solver.
In my classes, you’ll learn not just formulas or code but how to truly understand concepts, apply them, and build strong logical intuition.

I teach:
• 🔢 Mathematics: From algebra and calculus to applied problem-solving for real-world use.
• 💻 Computer Science: Coding fundamentals (Python, C++), algorithms, and logical thinking for beginners and intermediate learners.
• ⚛️ Physics: Mechanics, thermodynamics, and practical examples that make abstract ideas simple and visual.

As a Software Engineer and Master’s student in Engineering at Nagoya University, I bring both academic knowledge and hands-on experience from real projects. My teaching approach is interactive, visual, and deeply focused on understanding over memorization.

Let’s turn complex problems into clear, step-by-step insights — and make learning something you genuinely enjoy.

Amin

4.9

(69)

Python is the most in-demand programming language in the world right now — and one of the easiest to learn with the right guidance.
Whether you've never written a line of code or you're a student who needs to pass a programming course, this is a practical, no-fluff introduction that gets you writing real code from session one.
What we can cover depending on your goals:

Python fundamentals: variables, loops, functions, data structures
- Object-oriented programming (OOP)
- Data manipulation with pandas and NumPy
- Introduction to machine learning with scikit-learn
- Database management with SQL
- C and Java upon request
- MATLAB and R available for engineering/science students

Why learn with me?
I'm not a student teaching on the side — I'm a professional engineer who uses Python daily for data analysis, modeling, and automation. I know exactly which concepts matter in the real world and which ones you can skip for now.
Sessions are 100% personalized: I adapt the pace, the examples, and the exercises to your background and your goal — whether that's passing your university exam, building a project, or landing a job.

Reza

4.9

(69)

You will learn Systematic Reasoning & Logical Thinking which is a requirement for entering Computer Science program in many universities.
The book “Delftse Foundations of Computation” especially its second chapter will be the main source of our lesson, but other more in-depth books will be also covered if you want to improve even further on logical thinking.
The topics in our lesson include:
• Propositional Logic: Logical operators; Precedence rules; Logical equivalence; Implications in English; Exclusive or; Universal operators; Classifying propositions
• Boolean Algebra: Substitution laws
• Logic Circuits: Logic gates; Combining gates to create circuits; From circuits to propositions; Disjunctive Normal Form; Binary addition.
• Predicate Logic: Predicates; Quantifiers; Tarski’s world and formal structures;
• Deduction: Valid arguments and proofs; Proofs in predicate logic

If you have any additional questions before starting a class, please feel free to ask me. I am here to assist! :)

Florian

4.9

(69)

Experienced and patient teacher of logic for computer science.

I have taught logic, formal languages and automata theory to undergraduates for six years. My tutoring is adapted to the student's level and goals. Whether you need to learn logic for your studies, or you would simply like to know more about the subject, I will be more than happy to help you improve your understanding and skills.

Logic
The sciences presuppose a certain standard of rationality. An ability to distinguish between correct reasoning and claims that do not follow from the assumptions. In this class we study the basic principles of logic and apply mathematical techniques to the study thereof.
Topics include:
Propositional and Predicate Logic
Syntax and semantics
Natural deduction
Semantic tableaux
Correctness and soundness
Completeness

Formal languages and automata
A formal language is an abstraction of general characteristics of programming languages. Such a languages consists of a set of symbols together with some rules to determine whether a string made up out of those symbols is a member of the language.

Topics include:
Regular languages, context-free languages
Finite automata, pushdown automata, Turing machines
Regular expressions
Regular grammar, context-sensitive grammar
Pumping lemmas for regular and context-free languages

Baia

4.9

(69)

I teach Python specifically for finance and data applications - the kind used in economics, business analytics, and quantitative programs. This isn't a general "learn to code" course; it's built around real financial data, benchmarking, and the workflows you'll actually use in coursework or early career work.

Topics include:
Python fundamentals through a finance lens (data structures, functions, control flow).
Working with financial data and datasets.
Performance benchmarking and writing efficient code.
Applying concepts from Hilpisch's Python for Finance.

Vincent

4.9

(69)

With over seven years of experience in teaching Computer Science & Information Technology (ICT), I have developed a strong expertise in delivering high-quality education across multiple internationally recognized curricula, including Cambridge IGCSE, GCSE, A-Levels, O-Levels, and Checkpoint. My passion lies in equipping students with coding, cybersecurity, and digital literacy skills, ensuring they are well-prepared for the evolving demands of the digital world.

Expertise & Teaching Areas:
✅ Programming & Software Development: Python, Java, C++
✅ Cybersecurity: Ethical hacking, data protection, network security
✅ Digital Literacy: ICT applications, online safety, cloud computing
✅ Data Science & AI: Data analysis, machine learning fundamentals
✅ Web Development: HTML, CSS, JavaScript

Curriculum & Pedagogical Experience:
🔹 Cambridge IGCSE & GCSE ICT & Computer Science – Teaching core and extended syllabi, focusing on programming logic, databases, and networking.
🔹 Cambridge A-Levels & O-Levels Computer Science – Preparing students for advanced computing concepts, problem-solving, and algorithm development.
🔹 Cambridge Checkpoint ICT – Building foundational skills in digital technology and computer applications.

Professional Impact:
📌 Mentored students to achieve top grades in Cambridge ICT & Computer Science exams.
📌 Developed interactive lesson plans integrating real-world applications of technology.
📌 Conducted coding boot camps and cybersecurity workshops to enhance practical learning.
📌 Guided students in project-based learning, including app development and website design.

With a strong commitment to student-centered learning and technological innovation, I am dedicated to shaping future tech leaders and empowering learners with skills relevant to careers in technology, data science, and software development.

Mariem

4.9

(69)

Understanding algorithms is essential for anyone pursuing computer science or programming. In this course, I provide a structured approach to learning algorithms—from fundamental concepts like sorting and searching to advanced techniques such as dynamic programming and graph theory. Whether you're preparing for exams, coding interviews, or aiming to improve your problem-solving skills, this course is designed to build strong algorithmic thinking. Through practical examples and step-by-step explanations, I help students master the logic and techniques needed to write efficient and elegant code.

Zakariae

4.9

(69)

This course is aimed at non-Arabic speakers wishing to learn Arabic in a simple, progressive and practical way, while discovering Moroccan pronunciation (darija).
It is accessible to all beginner levels, and requires no prior knowledge.
Through an interactive method, you will learn:
The basics of the Arabic alphabet and correct pronunciation.
Essential expressions for everyday communication.
The construction of simple sentences (present, past, future).
Useful vocabulary: family, food, time, travel, emotions...
An introduction to Moroccan Darija, to understand and speak easily with Moroccans.
The course is suitable for:
Adults, students and travellers.
People wishing to discover Moroccan culture.
Learners seeking patient, clear and motivating support.
I provide :
Structured course materials (PDF + exercises).
Audio recordings to improve pronunciation.
Mini real-life scenarios for practice.
Personalized support to progress with confidence.
📚 Simple, clear and effective method
👨‍🏫 Support tailored to your pace

Raouf

4.9

(69)

Objective: To understand AI without fear, to use it to simplify one's life, to know how to identify digital traps, and to use Word, Excel, etc. without difficulty.

1: Demystifying AI (What exactly is it?)
AI is not a movie robot: Difference between fiction and reality.

How it works (simply): The image of the "giant library": AI has read billions of books and uses them to predict the continuation of a sentence or create an image.

Where is it already present? Spell checkers, Netflix/YouTube suggestions, GPS, and voice assistants (Siri/Alexa).

2: Using AI to make life easier
Conversing with AI (ChatGPT, Claude, Gemini):

Ask him to write an administrative email or a complex letter.

Summarize a long newspaper article or document.

Plan a travel itinerary or find recipe ideas with what's left in the fridge.

AI for creativity and memory:

Generate images to illustrate a birthday card (Midjourney, DALL-E).

Using AI to restore or colorize old family photos.

3: Learning to "talk" to AI (The Art of the Prompt)
The context method: Why "Give me a cake recipe" is less effective than "I am allergic to gluten and I am hosting 4 people, give me a simple chocolate cake recipe".

The expert's role: Learning to tell AI "Act like a travel guide" or "Act like an expert gardener".

4: Precautions and Critical Thinking (The Survival Guide)
"Hallucinations": Understand that AI can make false claims with complete certainty (never take medical or legal advice from AI without verification).

Privacy protection:

Never give sensitive data (social security number, passwords, bank details) to an AI.

Knowing that everything we write to the AI is potentially used to train it.

Spotting "Deepfakes":

How to recognize a doctored image or video (details on the hands, strange reflections, slightly metallic voice).

Verify the information: the golden rule of cross-referencing sources.

5: Ethics and Impacts (To go further)
Copyright: Who owns an image created by AI?

The environmental impact: The water and energy consumption of AI servers.

The future: Will AI replace us or assist us?

Wissem

4.9

(69)

I teach coding to beginners and intermediate students.
Lessons focus on logic, basic programming, and practical exercises.
Classes are adapted to the student’s pace.
Students can choose between website or mobile app development.Hands on dev

Ammar

4.9

(69)

A- TOPICS YOU CAN EXPLORE AND MASTER:
1- PYTHON FOUNDATIONS
• Variables, data types, operators, conditional structures, loops, functions, modules, files, exceptions, and object-oriented programming
• Lists, tuples, dictionaries, sets, comprehensions, debugging, and writing clear, reusable, well-structured code
• Jupyter Notebook, Anaconda, Visual Studio Code, virtual environments, and package management

2 — PROGRAMMING, ALGORITHMS, AND COMPUTER SCIENCE FOUNDATIONS
• Algorithmic thinking, problem decomposition, pseudocode, flowcharts, procedural programming, object-oriented programming, recursion, and modular program design
• Fundamental data structures including arrays, lists, stacks, queues, dictionaries/hash tables, sets, trees, graphs, and their appropriate use
• Searching, sorting, traversal, algorithm efficiency, computational complexity, Big-O notation, debugging, testing, code organization, and problem-solving strategies
• Practical programming exercises ranging from beginner problems to university-level algorithmic and computational challenges

3- DATA PREPARATION AND EXPLORATION
• NumPy and pandas for importing, cleaning, transforming, filtering, grouping, reshaping, and merging data
• Missing values, duplicates, outliers, inconsistent formats, data leakage, and data-quality validation
• Exploratory data analysis using descriptive statistics, Matplotlib, Seaborn, and graphical interpretation

4- MATHEMATICAL FOUNDATIONS
• Linear algebra, vectors, matrices, derivatives, optimization, probability, and statistics
• Loss functions, gradients, distance measures, regularization, likelihood, and model complexity
• Mathematical concepts are explained according to the learner’s level and the requirements of the selected algorithms

5- SUPERVISED MACHINE LEARNING
• Linear and polynomial regression, logistic regression, and regularized models
• k-nearest neighbours, decision trees, random forests, gradient boosting, support vector machines, and Naive Bayes classifiers
• Classification, regression, model assumptions, decision boundaries, feature importance, and interpretation of results

6- UNSUPERVISED LEARNING
• Clustering using k-means, hierarchical clustering, and density-based methods
• Principal component analysis, dimensionality reduction, anomaly detection, and pattern or structure discovery
• Method selection, evaluation of data structure, and interpretation of results without predefined labels

7- MODEL EVALUATION AND IMPROVEMENT
• Training, validation, and test sets; cross-validation; hyperparameter optimization
• Accuracy, precision, recall, specificity, F1 score, ROC–AUC, confusion matrices, MAE, MSE, RMSE, and R2
• Underfitting, overfitting, bias–variance trade-off, class imbalance, feature engineering, feature selection, scaling, and regularization

8- DEEP LEARNING
• Neural-network foundations, activation functions, forward propagation, backpropagation, and gradient descent
• Multilayer perceptrons, convolutional neural networks, recurrent neural networks, and Transformer foundations
• TensorFlow, Keras, or PyTorch depending on the learner’s project and working environment

9- ARTIFICIAL INTELLIGENCE APPLICATIONS
• Natural language processing, text classification, embeddings, sentiment analysis, and foundations of language models
• Computer vision, image classification, fundamental principles of object detection, and image preprocessing
• Recommendation systems, forecasting, anomaly detection, intelligent automation, and decision-support applications

10- GENERATIVE AI AND LARGE LANGUAGE MODELS
• Transformer architecture, tokens, embeddings, attention mechanisms, prompt engineering, Retrieval-Augmented Generation (RAG), and model evaluation
• Use of artificial-intelligence APIs, vector databases, document-retrieval systems, and structured AI-enabled workflows when relevant
• Reliability, hallucinations, bias, privacy, responsible use, and appropriate human validation

11- TOOLS AND LIBRARIES
• Python, NumPy, pandas, Matplotlib, Seaborn, scikit-learn, SciPy, Statsmodels, TensorFlow, Keras, and PyTorch
• Jupyter Notebook, Anaconda, Visual Studio Code, Git, GitHub, SQL, Excel, and Power BI when useful to the project
• Additional libraries may be introduced depending on the selected specialization and dataset

12- PROJECTS, RESEARCH, AND INTERVIEW PREPARATION
• Complete projects covering data preparation, model development, evaluation, interpretation, and presentation of results
• University assignments, dissertations, theses, research projects, portfolio projects, technical interviews, and professional applications
• Code review, debugging, documentation, reproducibility, model comparison, and communication of results

-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
B- PERSONALIZED TUTORING: LEARNING HOW TO REASON
Machine learning and artificial intelligence become much more accessible when mathematics, algorithms, Python code, data, and real-world applications are clearly connected.

My lessons help you move beyond simply copying code or using models as “black boxes.” You will learn how to define the problem correctly, prepare the data, select an appropriate algorithm, understand how it works, train and evaluate the model, diagnose errors, improve performance, and interpret results rigorously and responsibly.

Each lesson is personalized according to your current level, mathematical background, programming experience, dataset, university work, research project, interview preparation, or professional objective. We begin by identifying your existing knowledge, software environment, expected outcomes, and main conceptual or technical difficulties. We then establish a structured learning plan.

The first lesson combines a discussion of your background, objectives, and tutoring needs; an initial assessment of your current knowledge; personalized planning and organization of future sessions; and a short trial lesson to determine the most effective learning approach.

A typical session may include conceptual explanation, development of mathematical intuition, live coding, guided implementation, model evaluation, technical problem solving, and a concise summary of the next steps.

You may work with your own dataset, university assignment, research project, or professional problem, provided that confidential information is handled appropriately. I can also provide structured examples and datasets suited to your level.

My goal is not simply to help you run an algorithm. It is to help you understand why it is appropriate, how it learns from data, how to evaluate it correctly, why it may fail, and how to build a reliable, interpretable, and scientifically rigorous solution.

Laith

4.9

(69)

Want to break into systems, legally? Learn penetration testing from someone who does it for a living.

I'm a cybersecurity engineer with 150+ penetration tests and vulnerability assessments for government, financial, and telecom organizations. I hold CRTP, eWPT, and eJPT certifications, and I'll teach you the same methodology I use on real engagements. No boring theory dumps, just live, hands-on practice.

You'll learn:

The pentesting process: scoping, recon, scanning, exploitation, and reporting
Network and web application testing basics
Common vulnerabilities like SQL injection, XSS, and broken authentication
Core tools: Nmap, Burp Suite, Nessus, Metasploit, and Wireshark
How to document findings and write reports that clients actually act on
How to build a home lab and keep practicing on your own

Perfect for: beginners, students, career changers, developers, IT staff, and anyone preparing for eJPT, PNPT, OSCP, or CEH.

You'll walk away with a clear pentesting workflow, real hands-on skills, and a solid roadmap for a career in offensive security.

Basic computer skills are enough, and networking knowledge is a plus. Book your first session and let's start hacking (ethically)!

منال

4.9

(69)

📊Microsoft Office: To establish your office skills, manage data via Excel, write professional reports with Word, and prepare impressive presentations with PowerPoint.

📐 AutoCAD: To learn engineering drawing and design two-dimensional and three-dimensional plans with high accuracy and speed.

🛣️ Civil 3D: To learn road design, network design, surveying, and quantity surveying in a scientific and practical way

Juan

4.9

(69)

I hold a degree in Management and Software Programs (Rey Juan Carlos University) and have over 20 years of experience in IT and cybersecurity, as well as extensive experience as a vocational training instructor. I help you learn IT in a clear, practical way, without unnecessary technical jargon, whether you're starting from scratch or want to delve deeper into networks, operating systems, or security.

METHODOLOGY
The classes are 100% practical and adapted to your pace and goals. We always start from your current situation (your computer, your work, your questions) and practice with examples and guided exercises. At the end of each session, I provide a summary of what we've covered and, if you wish, optional exercises to reinforce the material. I explain things in simple language, repeat as many times as necessary, and we progress step by step.

SYLLABUS AND LEVELS
- Basic computer skills (beginner): computer handling, files and folders, internet, email, safe use of mobile phones and computers.
- Office automation (beginner and intermediate): Word, Excel and office tools; formulas, tables, charts and data organization. Also advanced level Excel.
- Operating systems (intermediate): Windows and Linux, installation, configuration, users and permissions, maintenance and troubleshooting.
- Networks (intermediate and advanced): network fundamentals, IP addressing, switching and routing, VPN, WiFi and firewalls.
- Cybersecurity (all levels): personal and business protection against phishing, malware and fraud, passwords and backups, regulations (ISO 27001, ENS, GDPR), hardening, vulnerability analysis and basic ethical hacking, SOC and SIEM. Preparation for professional certifications such as IFCT0109 Information Security.
- Programming and data (on request): Python, scripting with PowerShell and Bash, SQL databases.

WHO IS IT FOR?
For children and teenagers who want to learn how to use technology safely, for adults who need to be better at using computers, for older people who want to overcome their fear of technology, for professionals and freelancers who need to improve their office skills, for vocational training students or those pursuing professional certificates, and for those who want to get started in cybersecurity or protect their company.

FIRST CLASS
In the first class, we'll discuss your goals, assess your current level, and answer your most pressing questions. From there, we'll design a personalized learning plan, outlining the topics, pace, and frequency of your classes. You'll leave the first session with a clear path forward and some initial learning.

ONLINE AND IN-PERSON CLASSES IN MALAGA
I offer online classes via video call from anywhere in Spain and in-person classes at your home in Malaga and the surrounding area. In both cases, the content and personalized attention are the same. Write to me and tell me what you need.

Abdul

4.9

(69)

Spending hours every month cleaning the same Excel reports? Or preparing for the PL-300 (Microsoft Power BI Data Analyst) exam and not sure where to start? I teach working professionals and career changers how to use Power BI and Excel the way they're used at work, step by step and in plain language.

What you'll learn (tailored to your goal):
• Power Query: clean messy data (extra spaces, wrong data types, duplicates, text numbers) and set it up so next month is just "Refresh"
• Data modelling: star schema, relationships and a proper Date table
• DAX: measures, CALCULATE and time intelligence, explained so you understand why, not just copy formulas
• Dashboards: clear visuals, slicers, drill-down and Actual vs Target reports
• Power BI Service: publishing, refresh and sharing
• PL-300 exam practice: exam-style questions with explanations

How I teach:
I explain each idea before we click, then we build it together on a realistic dataset, and then you try it yourself. You get clear notes after each lesson. If you bring your own work file (with sensitive data removed), we can use it so you solve your real problem.

About me: Data Science Master's student and BI analyst. I built Power BI and Excel reporting for companies, and recently automated a finance team's monthly SAP report with Power Query so it now updates with one click.