#1 Data Science Tutoring
Private Data Science Tutoring, From Zero to Job-Ready
One student, one working data practitioner as your mentor. Learn Python, data analysis, visualization, and machine learning through real projects until you have a portfolio you can be proud of. Online with pair coding or in person at home, from Rp98,000 per 60-minute session.
180+
tutors
1,400+
students
4.9
rating · 728 reviews
60+
cities
What is Data Science Tutoring?
Data science tutoring is one-on-one private guidance for learning how to turn data into decisions and predictions. The material covers Python for data, data cleaning and analysis, visualization, applied statistics, and machine learning. Learning is project-based with real datasets, guided by working data practitioners, at Rp98,000 per 60-minute session, online or in person.
- One student, one mentor, pacing from statistics to machine learning that follows you
- From basic Python all the way to complete machine learning
- Learn through real projects with genuine datasets, going beyond theory
- Every module produces an analysis for your portfolio
- Suitable for complete beginners and for those switching careers into data
Services
Set Up How You Learn Data Science
In person at home, online with screen sharing, or a small group with friends. Match it to your schedule and your coding rhythm.
In-Person Data Science Tutoring
The mentor comes to your home for hands-on guidance while you write code and analyze data.
Rp 158.000/session
120 minutes
- Mentor comes to your home
- Hands-on guidance while coding and analyzing
- In-person notebook review
- Flexible schedule that suits you
Online Data Science Tutoring
Learn via Zoom with screen sharing and live notebook review, perfect for any city.
Rp 124.000/session
90 minutes
- No transport costs, more affordable
- Two-way screen sharing and pair coding
- Session recordings you can replay
- Available for students living abroad
Small-Group Data Science Tutoring
Learn together with 2-3 friends on collaborative analysis projects at a lighter cost.
Rp 158.000/session
120 minutes
- 2-3 students per group
- Team projects with a shared dataset
- The base rate is split fairly: the per-student discount appears automatically in the form
- Learn Git and notebook collaboration
Data Science Learning Stages
Four progressive stages, from your first line of Python to a running machine learning model.
Python & Data Foundations (Complete Beginner)
Never written code beforeGet to know Python and how to think with data. You learn basic syntax and start working with tabular data using pandas before moving on to analysis and models.
Subjects:
Python basicsNumPy and pandasReading data (CSV, Excel)Jupyter Notebook
Focus Areas:
- Comfortable writing Python code
- Working with tabular data
- Understanding data types and structures
- Working neatly in a notebook
Data Analysis & Visualization
Reading the story behind the dataClean up messy data and uncover patterns through exploratory data analysis. You learn to present findings with clear charts and basic statistics.
Subjects:
Data cleaningExploratory data analysisVisualization (Matplotlib, Seaborn)Descriptive statistics
Focus Areas:
- Cleaning real-world data
- Finding patterns and anomalies
- Creating charts that tell a story
- Drawing conclusions from data
Machine Learning
Making data predictStep up to modeling: building prediction and classification models with scikit-learn, then evaluating their performance. At this stage you understand the complete machine learning workflow.
Subjects:
Supervised learningRegression and classificationscikit-learnModel evaluation
Focus Areas:
- Training your first prediction model
- Choosing the right algorithm
- Measuring accuracy correctly
- Avoiding overfitting
Projects & Job Readiness
Work you can show offWork on a complete final data project from raw dataset to insights and model, then build your portfolio plus preparation for entering the workforce or a data internship.
Subjects:
End-to-end projectPortfolio and GitHubCommunicating resultsData interview preparation
Focus Areas:
- A complete data project in your portfolio
- A tidy GitHub for recruiters
- Able to explain results to non-technical people
- Interview and internship preparation
Data Science Tutoring Curriculum
Four core modules arranged step by step, all project-based with real datasets.
The mentor tailors the modules to your goals. Those who want to focus on analysis will go deeper into EDA and visualization, while those aiming for machine learning will add more modeling.
Python for Data
The foundations of Python and manipulating tabular data with pandas, every data scientist's main tool.
- Python syntax and data structures
- NumPy for numerical computing
- pandas: DataFrames and data operations
- Reading from various data sources
Analysis & Visualization
Cleaning, exploring, and visualizing data so it tells a clear story.
- Data cleaning and handling missing values
- Exploratory data analysis
- Matplotlib and Seaborn
- Descriptive statistics and correlation
Machine Learning
Building prediction and classification models and evaluating them correctly.
- Supervised learning: regression and classification
- scikit-learn workflow
- Train-test split and cross-validation
- Evaluation metrics and basic tuning
Projects & Portfolio
Weaving all the skills together into a complete, job-ready data project.
- End-to-end project with a real dataset
- Git and GitHub for data
- Storytelling and presenting results
- Portfolio and interview preparation
Who It Is For
Student Profiles Suited to Learning Data Science
Career Switcher
Professionals from other fields who want to move into the data industry. The private format lets you learn between work commitments with clear targets and a real portfolio.
Recommended:
A roadmap from Python to machine learningA mentor who understands the transition into a data career
University Students & Fresh Graduates
Students from various majors who want practical data skills, as well as fresh graduates preparing a portfolio to apply as a data analyst or data scientist.
Recommended:
Focus on projects and a GitHub portfolioGuidance on data analysis for your thesis
Professionals Looking to Level Up
Employees who want to make data-driven decisions, automate analysis, or add analytical skills to their current job.
Recommended:
Focus on practical analysis and visualizationCase studies tailored to your line of work
High School & Vocational Students
Students interested in data and technology early on, who want to get to know Python, or are preparing to enter data- and computer-related majors.
Recommended:
Start with Python and data logicFun projects matched to the student's interests
Why Us
Reasons to Learn Data Science With EduPoint Mentors
Our private format chases one end result: you can run a data project on your own and have a portfolio that proves it.
One Student, One Mentor
You set the pace, asking freely and moving from statistics to machine learning without waiting for a class.
Working Data Practitioners
Learn from people who genuinely work on data projects, complete with real workplace practices.
Project-Based Learning
Every module uses a real dataset and produces a genuine analysis. You learn by doing, going beyond just watching.
Mastering the Complete Workflow
From understanding the problem, to processing data, to communicating results. No more disconnected pieces of material.
Job-Ready Portfolio
Graduate with a tidy data project on GitHub, ready to show to recruiters.
Transparent Per-Session Pricing
Open, per-session pricing, so you can build from statistics basics without a long package.
Selected Data Science Mentors
Our mentors are working data practitioners as well as top students and alumni in statistics, computer science, and mathematics from leading Indonesian universities, experienced in guiding learners from scratch.
Tutor Qualifications
- Working data practitioners and alumni of Statistics, Computer Science, and Mathematics from leading universities
- Experienced in real data and machine learning projects
- Passed technical skills screening and a teaching test
- Skilled in the modern stack: Python, pandas, scikit-learn, plus SQL and visualization
Himawan H.
Statistics, Institut Teknologi Sepuluh Nopember
Statistics that make sense“Himawan explains the basics of statistics with close examples, so numbers and formulas make sense before moving into data analysis.”
Karina K.
Statistics, Institut Teknologi Sepuluh Nopember
Cleaning up raw data“Karina stresses the often-skipped step of cleaning data, because good analysis always starts from clean data.”
Reta R.
Statistics, Universitas Gadjah Mada
Turning data into a story“Reta trains students to read data and turn it into a story others can understand, the heart of an analyst's work.”
Charles D.
Statistics, Universitas Brawijaya
Visuals that speak“Charles teaches making charts that deliver the message at once, so findings from data are easy to grasp at a glance.”
Angger A.
Statistics, Universitas Diponegoro
Python for data work“Angger introduces Python and data libraries step by step, so students can process data themselves with confidence.”
Sony E.
Applied Data Science, Politeknik Elektronika Negeri Surabaya
From data to decisions“With an applied data-science background, Sony shows how data drives real decisions, so learning feels immediately useful.”
Testimonials
How Students Broke Into the World of Data
From zero coding to a data analyst internship, these are the stories of those who took the data science journey with EduPoint mentors.
I come from an economics background with zero coding experience. In 7 months of private tutoring, I now have 3 analysis projects in my portfolio and got accepted for an internship as a data analyst. My mentor was patient explaining Python from the basics.
Hansen H.
Career switcher from economics • Jakarta
Self-teaching from online courses left me confused about the order. With a mentor, the roadmap was clear from pandas to machine learning. Each session had a target and a small project I worked on right away.
Dewi M.
Statistics student • Bandung
My thesis needed data analysis and a prediction model, but I was stuck. The EduPoint mentor guided me from data cleaning to interpreting the results. My defense went smoothly because I truly understood the analysis.
Nadya O.
Final-year student • Surabaya
I am a manager who wanted to read data myself without always asking my team. The private tutoring focused on analysis and visualization suited to my work needs. Now I can build my own dashboards for reports.
Arif M.
Professional, looking to level up • Tangerang
My work schedule is packed, so evening online tutoring helped a lot. The sessions are recorded so I can replay them. Slow but consistent, and now I am comfortable with pandas and scikit-learn.
Cantika N.
Employee, learning while working • Depok
I enjoy the statistics side and my mentor steered me straight into modeling. Now I understand when to use regression or classification and how to evaluate them. It feels like opening up a new way of thinking.
Budi N.
Mathematics student • Semarang
My child is in university and wants to enter the data field. The mentor guided them from Python to real projects, and gave feedback diligently. They have become more confident applying for data internships.
Gina N.
Parent of a university student • Jogja
What I love is that the learning is genuinely project-based with real datasets. Each finished module produces a real analysis that goes into my portfolio. So learning feels productive, with no theory left hanging.
Vina S.
Career switcher from marketing • Medan
Data Science Tutoring Fees
Data science mentoring charges per hour, plainly stated. Session length (60/90/120 minutes) and a monthly cadence of 4-28 meetings are yours to set; the final total is displayed while you enroll.
Starting from
Rp 79.000 / hour
Final price is set at registration.
This is the lowest hourly rate, derived from the 28-session monthly plan at 120 minutes per session. Per-session prices (60, 90, or 120 minutes) appear in the format options above.
Flexible payment — QRIS, Virtual Account, Alfamart, Indomaret, transfer & e-wallets.
Prices may adjust based on your learning focus, location, and tutoring format. Contact us for an exact quote.
Data Science Tutoring Availability
Online Tutoring
Online WorldwideOnline data science tutoring is available for students across Indonesia and abroad.
- Two-way screen sharing and pair coding
- Sessions are recorded and can be replayed
- No transport costs
In-Person Tutoring
All CitiesIn-person data science tutoring, with the mentor coming to your home in the following cities.
Jakarta45+ tutorsBandung24+ tutorsSurabaya20+ tutorsDepok16+ tutorsTangerang15+ tutorsBekasi14+ tutorsBogor10+ tutorsSemarang10+ tutors
+4 more citiesStudent Achievements
Our Students' Career Journeys
Real stories from those who changed their career direction through data science.
Success
From Admin to Data Analyst
Anisa R.
Success
A Student with a Machine Learning Portfolio
Ismail H.
Success
A Professional Who Moved into a Data Role
Nisa N.
FAQ
What Prospective Students Ask Before Starting Data Science
From fees and math requirements to laptop specs and the path to data analyst, we answer it all here.
Complete Guide
Complete Guide to Data Science Tutoring
Guides & Tips
Supporting articles to help you decide and maximize learning outcomes.
Data Science Learning Roadmap From Scratch for Beginners Until Your First Project
Seven sequential stages that carry a complete beginner from statistics and Python foundations to training your own machine learning models and weaving them into one end-to-end project.
Data Scientist vs Data Analyst vs Data Engineer: The Differences
Three professions born from the same data pipeline, each with a distinct focus and skill set.
How to Build a Data Science Portfolio for Beginners
Recruiters judge skill from work they can see. A strong portfolio holds projects that answer real questions, are neatly documented, and reveal how you think.
Learning SQL for Beginner Data Analysts: A Clear Step Order
A learning map that starts from five core commands and practice on real data, built for people just entering the world of data.
Self-Taught Data Science Roadmap for Beginners
Build a measurable, independent learning path, from Python basics to your first portfolio project.
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Your First Step Toward a Data Science Career Starts Here
Free consultation with our team to pin down where to begin, from Python to machine learning, and to find the data mentor who suits you best.
Free consultation with no commitmentWorking data practitionerstutor changes are always free