Excel Power Query & Automation: Turn Hours of Manual Reporting into One Click

From 51 C$ /h

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.

Extra information

Bring a laptop with Power BI Desktop installed (free, Windows) and Microsoft Excel. Tell me your goal before the first lesson (exam, job or a specific report) so I can prepare.

Location

Online from Malaysia

About Me

Hi, I'm Abdul. I help people use Power BI and Excel the way they're actually used at work.

Most of my students are working professionals and career changers: accountants tired of copy-pasting the same report every month, analysts preparing for the PL-300 exam, and people moving into a data analyst role. Many of them feel stuck because tutorials show the clicks but never explain why. That's what I focus on.

My lessons follow a simple rhythm: I explain the idea in plain language, we build it together on a realistic dataset, and then you do it yourself while I guide you. I check that you understand the reasoning, not just the steps, because that's what makes it stick at work and in the exam. After each lesson you get clear notes and key terms to review.

I'm patient and I enjoy questions. No question is too basic. If you bring your own work file (with sensitive data removed), we can solve your real problem together.

I especially like working with motivated adults who have a clear goal: passing PL-300, automating a report, or getting job-ready as a data analyst.

Education

Master of Computer Science (Data Science), Universiti Teknologi Malaysia (UTM), 2025–2027 (in progress)
Bachelor of Engineering (Chemical Engineering), National University of Sciences and Technology (NUST), Pakistan, 2020–2024

Experience / Qualifications

• Excel & Power BI Tutor (PL-300 exam prep), online, 1:1 with working professionals: Power Query, data modelling, DAX, dashboards
• Freelance Power Query automation: automated a finance team's monthly SAP cost report so it refreshes with one click and reconciles to the original
• Sales Analyst, NovaPack Pvt Ltd (Dec 2024 – Jul 2025): automated Power BI dashboards, SQL analysis, sales forecasting
• Junior Data Analyst, Logo Official (Sep – Dec 2024): Power BI and Excel dashboards for senior management
• Certifications: [exact names of your 2 AWS certifications]; Data Analytics (atomcamp, 2024)
• Skills: Power BI, Power Query, DAX, Excel, SQL, Python

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

45 minutes

60 minutes

90 minutes

120 minutes

The class is taught in

English

Urdu

Skills

Microsoft excel

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

Salah

4.96

(28)

Optimize Your Efficiency with Microsoft Office: Unleash Your Creativity at Every Level!

If you're looking for a solution to improve the efficiency, creativity and productivity of your daily tasks, look no further than Microsoft Office.

Why Choose Microsoft Office?

Unleash Your Creativity: Word, Excel, PowerPoint and many other applications give you powerful tools to bring your ideas to life, whether you're creating professional documents, building impactful financial dashboards or designing impressive presentations.

Save Time with Automation: Excel simplifies complex tasks with smart formulas, pivot tables, and other nifty features.

Available Anywhere: Whether you're in the office, on the road, or at home, Microsoft Office is accessible on all your devices, allowing you to work wherever and whenever you want.

Join the Microsoft Office Revolution!

Don't let daily challenges slow down your progress. Invest in the power of Microsoft Office to unlock your full potential.

Transform the way you work, create easily, and reach new heights with Microsoft Office. Sign up now to master Microsoft Excel, Microsoft Word, and Microsoft PowerPoint at every level, whether you're beginner, intermediate, or advanced.

Florian

4.96

(28)

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

4.96

(28)

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

4.96

(28)

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.

Dr.Ibrahim

4.96

(28)

This course introduces students to the fundamentals of Information and Communication Technology (ICT) and its role in modern society. Topics include computer hardware and software, digital communication tools, internet technologies, data management, cybersecurity, and emerging trends. Students will gain practical skills in using productivity software, conducting online research, and understanding the ethical and responsible use of digital resources. The course emphasizes both technical proficiency and digital literacy, preparing learners to confidently navigate and contribute to a technology-driven world.

Mariem

4.96

(28)

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.

Amin

4.96

(28)

Data skills can change your career, and you don't need to be a "math person" or have a technical background to learn them. If you can use a computer and you're curious, you can do this. In just 10 hours of one-to-one lessons, you'll go from "I don't know where to start" to analyzing real data on your own.

Maybe you're a student who needs to analyze data for a course or a thesis. Maybe you're looking for your first job in data, finance or business and want a skill that employers ask for. Maybe you already use Excel every day, but your reports take hours and you suspect there's a faster way. Or maybe you've never written a line of code and the idea feels intimidating. This class is built for all of you, and every lesson starts from where you are today.

I'm an engineer, and I work with data, statistics and programming (SQL, Python, R, Excel) every day. I don't teach theory for its own sake. I teach the way I use these tools in real work: you get a real question, a real dataset, and a clear method for turning one into the other.

In 10 hours, you will be able to:

Write SQL queries on your own. Select, filter, sort and group data, combine several tables with JOINs, and answer real questions such as "which product sold the most each month?"
Clean and analyze data in Excel. Use lookup formulas, conditional calculations and PivotTables, and build clear charts, instead of spending hours on manual work.
Build your first Power BI dashboard. Import data, clean it with Power Query, create interactive visuals, and share a report that looks professional.
Explain your results. Turn a business question into a query or a dashboard, check that your results make sense, and present them to someone who doesn't know the data.
Show a finished project. Leave with a portfolio-ready analysis you can use in an interview or in your thesis.

How the 10 hours are organized (we adapt this to your level and goal)

Hours 1-2: Foundations. We define your goal, check your level, and cover your first SQL queries (SELECT, WHERE, ORDER BY).
Hours 3-4: SQL in depth. Grouping and summarizing data, JOINs across tables, and cleaning messy data.
Hours 5-6: Excel for analysis. Advanced formulas, PivotTables, and charts.
Hours 7-8: Power BI. Importing and cleaning data, building visuals, and creating an interactive dashboard.
Hours 9-10: Your project. We put everything together on a realistic dataset (sales, finance, HR or your own data), and I give you feedback and a plan for what to practice next.

If you already know some Excel or SQL, we skip what you know and spend more time on what you need. If you want to go deeper later (for example advanced DAX, Python or statistics), we can continue from the same foundation.

How the lessons work

Every lesson is one-to-one and tailored to you. You practice on your own screen with my guidance, so you learn by doing rather than by watching. Between sessions I can give you short exercises if you want extra practice, and you can send me questions anytime. If you have your own files or work data (anonymized, of course), we can use them, which makes the learning much more relevant. Otherwise I provide practice datasets.

I explain in English or French (or Arabic if that's easier for you), and I'm patient. There are no silly questions. If something doesn't click, I'll explain it another way until it does.

Who this class is for

Students in business, economics, engineering, science or social sciences
Job seekers and career changers who want a first step into data analysis
Professionals who want to automate reports and work faster
Complete beginners. No previous experience with SQL or Power BI is needed.

Raouf

4.96

(28)

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

4.96

(28)

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

Laroussi

4.96

(28)

Session 1: Revolutionizing your Scientific Writing with LaTeX & AI
Duration: 2 Hours | Level: Beginner | Tools: Overleaf + AI**

First Hour: Foundations and Cloud Environment (60 min)

1. Introduction to LaTeX Philosophy (15 min)

- The "WYSIWYM" concept:** Explain the difference between Word (*What You See Is What You Get*) and LaTeX (*What You See Is What You Mean*). Why content takes precedence over form.
- Key advantages:** Unrivaled typographic quality, automatic reference management, stability on long documents (theses), and free of charge.
- The structure of a file:** Distinction between the **preamble** (the brain: settings and packages) and the **body of the document** (the heart: text).

2. Immersion in Overleaf (25 min)

- Configuration:** Creation of an account and first project "Blank Project".
- Exploring the interface:** The file panel (left), the code editor (middle) and the PDF preview (right).
- Real-time collaboration:** How to share a project and leave comments (like on Google Docs).
- History and versions:** How to revert to a previous version in case of a compilation error.

3. Practical Workshop: My First Document (20 min)

* Writing basic commands: `\documentclass`, `\usepackage[french]{babel}`, `\title`, `\author`.
* Compilation of the document and observation of the result.
* Structuring: Use of `\section` and `\subsection`.

Second Hour: Mathematics and the Magic of AI (60 min)

4. The Power of Mathematics (20 min)

- Mathematical modes:** Difference between the text (`$...$`) and the centered block (`\[...\]`).
- Essential syntax:** Fractions `\frac{}{}`, exponents `^`, indices `_`, and roots `\sqrt{}`.
- Introduction to AMS packages: Why amsmath and amssymb are essential for professional rendering.

5. From hand to screen: AI at the service of LaTeX (30 min)

- Presentation of OCR tools:** Use of **Mathpix Snip** (the leader) or models like Gemini/ChatGPT to transform a photo into code.
- Concrete demonstration:
1. Take a picture of a complex handwritten formula (e.g., an integral with matrices).
2. Use AI to generate the corresponding LaTeX code.
3. Correction and insertion: Learn to check the AI-generated code before copying and pasting it into Overleaf.

6. Conclusion and Q&A (10 min)

* Summary of achievements.
* Resources for further exploration
* Definition of the exercise for the next session.

Ammar

4.96

(28)

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

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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.

منال

4.96

(28)

📊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

Hayat

4.96

(28)

Vous voulez analyser vos données avec Excel, sans vous perdre dans les formules ? Ce cours en ligne vous guide pas à pas, avec des exemples concrets et des exercices pratiques.

Vous apprendrez à :

organiser et nettoyer vos données (tri, filtres, suppression des doublons)
utiliser les formules essentielles (SOMME, SI, NB.SI, MOYENNE, RECHERCHEV / RECHERCHEX)
résumer vos données avec les tableaux croisés dynamiques
créer des graphiques clairs et présenter vos résultats

Le cours s’adapte à votre niveau et à vos besoins (études, travail, projet personnel). Je suis data analyst et j’utilise l’analyse de données au quotidien, ce qui me permet de vous montrer des cas pratiques.

Juan

4.96

(28)

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.

Roobini

4.96

(28)

Hi! I'm Roobini, a technology professional, mentor and passionate educator who enjoys making learning simple, practical and interesting.

I offer personalized lessons in Communication Skills, Computer Basics and Mathematics, designed for school students, college students and beginners.

My teaching approach focuses on understanding concepts, building confidence and applying knowledge through practical examples.

What I teach:

1. Communication Skills
- Spoken English and everyday communication
- Public speaking and presentation skills
- Vocabulary, grammar and sentence formation
- Interview preparation and interpersonal skills
- Confidence building

2. Computer Skills
- Computer fundamentals and digital literacy
- MS Office and basic productivity tools
- Internet and essential digital skills
- Programming fundamentals
- Introduction to technology and AI

3. Mathematics
- Basic mathematics and arithmetic
- Algebra and geometry fundamentals
- Logical reasoning and problem-solving
- School-level mathematics
- Concept-based practice and exam preparation

My Teaching Methodology
- Personalized lessons based on each student's learning level.
- Simple explanations with real-life examples.
- Interactive sessions and practical exercises.
- Regular practice, feedback and progress tracking.
- A friendly and supportive learning environment.

With a background in Computer Science Engineering, enterprise technology and professional communication, I aim to help every learner develop knowledge, confidence and skills for the future.

Let's learn, practice and grow together!