A problem worth modeling
Identify a significant data science problem and put it in terms that a machine learning model can address.
Partners and press
Overview
A model is the last step. The question comes first.
A two-hour case study that follows one machine learning project from end to end: choosing a problem worth solving, working with Python libraries, preparing the data, and building statistical and predictive models.
It runs in the order a project does. Define the problem, get to know the data and its gaps, model relationships and causation with regression, then build, interpret and refine a predictive model.
2Hours
5Modules
4.9Academy rating
10,000+Students
What you’ll learn
Learn all the way down.
Learn all the way down.
Perform when it matters.
Data you can trust
Define and explore variables, find missing data and outliers, split the data, and check it meets the statistical assumptions a model relies on.
Relationships and causation
Apply regression analysis and other statistical models to understand how variables relate, and what the data says about cause.
A predictive model, refined
Build a model that forecasts from historical data, interpret its results, and plan the next steps in the machine learning pipeline.
Course outline
Five modules, from the problem
Five modules, from the problem
to a model you can interpret.
Identify and articulate a significant data science problem that machine learning can address, and set the project up before any model is built.
The Python libraries that carry data manipulation and machine learning work: Pandas, NumPy and Scikit-learn.
Define and explore variables, find missing data and outliers, split the data, and check that it meets the statistical assumptions a model needs.
Use statistical models, regression analysis among them, to understand relationships and causation in the data and draw conclusions from it.
Predictive modeling to forecast trends from historical data: build and refine a model, interpret its results and plan the next steps in the pipeline.
Your instructor
Instructor · LUNARTECH
Tatev Aslanyan
Tatev brings industry experience, advanced AI/ML degrees and a reputation as a thought leader in data science to LUNARTECH. She holds Bachelor’s and Master’s degrees in STEM, and her publications in top journals and presentations at international conferences showcase her expertise.
How you get there
Top-tier roles go to people who can do the work.
Top-tier roles go to people who can do the work.
Here’s how you get there.
Frame the problem first.
Decide what question is worth asking, and whether machine learning is the way to answer it.
Know the data before modeling.
Explore the variables, find the gaps and outliers, and test assumptions before fitting anything.
Model it, then predict.
Fit regression to see relationships, then build a predictive model and read what it says.
Support
Support at every stage.
Support at every stage.
You won’t be working through this alone.
Before you start
Try it first.
A 3-day free trial opens a selection of the content. Your card is only charged once it ends.
While you learn
Mentors within reach.
Stuck on a concept? Reach out to a mentor whenever you need help.
While you learn
One-on-one sessions.
On the yearly plan, one-on-one sessions give you dedicated support.
Any time
A team behind you.
Write to info@lunartech.ai at any point, from your trial onwards. If your employer is funding you, we’ll set it up with them directly.
All the way through
A schedule that fits around your life.
2 hours in totalYour own paceFrom anywhereAt any hour
After the last lesson
Stay in the network.
Your alumni network stays with you: ongoing support, opportunities and industry insight.
Career support
Career support, past the last lesson. Coaching, a sharper resume, real interview preparation and the people to know.
Career direction
Tailored coaching helps you decide where to aim and how to get there.
Strong portfolio
Hands-on projects become work you can show, not just claim.
Resume and profile
Personalized refinement, so what you send says what you can actually do.
Interview preparation
Preparation for the questions that decide it, so you walk in ready.
Network and search
Connections with industry leaders, and an alumni network that stays with you.
Reviews
Real stories from the community.
LUNARTECH Academy has been the most empowering learning experience of my life, giving me a clear, structured path from the absolute basics to building real-world AI systems with confidence.
Your page is fantastic. As a bachelor’s student in Data Science now accepted for a master’s at UConn, your work has been a real source of motivation.
The programme’s clear, bite-sized content and practical projects dramatically improved my speed from fuzzy idea to MVP and my ability to communicate AI value. I followed the system, and it works.
I really appreciate your teaching style and the way you break down complex topics. It has been incredibly helpful.
After years working mainly with R for econometrics, I found your Python machine learning course a refreshing and engaging way to learn Python.
As a Data Science graduate, I want to thank you for the effort you put into making videos to support growing data scientists.
I’ve been following your work since taking your machine learning course, and I’m impressed by your practical approach to applying AI.
Why choose us
Built around how you actually learn.
One standard behind every course, from the first lesson to long after the last.
Hands-on practice
Apply every idea to real problems, so it becomes something you have used, not only seen.
Industry-aligned curriculum
We keep courses current with the tools, techniques and skills the field asks for.
Flexible learning
Study at your own pace, from anywhere, at any hour.
Certificate of completion
Finish the course and earn a certificate that shows what you have learned.
Focus on your success
Personalized learning plans and support structures carry you through the hard parts.
Lifetime alumni network
Stay connected after you finish, with ongoing support, opportunities and industry insight.
Your certificate
It doesn’t raise its voice. Neither will you.
Finish the course and it is issued in your name, under our signature. There is no other way to get one.
Certificate of completion
Your Name
Machine Learning Case Study
LUNARTECH RISE Academy
Pricing
This course comes with the membership.
This course comes with the membership.
So does everything else.
One membership opens every course, certification, workshop and masterclass in the Academy. Every plan starts with a 3-day free trial.
3 days free, then $29.97 a month. Your card is only charged once the trial ends.
Included in every plan
- Every course in the Academy
- Every certification course
- Workshops and masterclasses
- A certificate of completion
- A 3-day free trial
- Learning at your own pace
- The lifetime alumni network
- Upgrades at any time
In practice
Five modules. Four professions.
Five modules. Four professions.
One project, from question to forecast.
Every role uses all five modules. Here’s where each one leans hardest, and where its work ends up.
- 01The problem
- 02Python tools
- 03Exploration
- 04Causal analysis
- 05Prediction
-
Frames the problem before reaching for a model. Checks the data and the assumptions behind every result.
The problem, Exploration, Causal analysis, Prediction
Data science teams, Product teams
-
Builds and refines predictive models in Python. Plans what comes next in the machine learning pipeline.
Python tools, Prediction
Data science teams, Product teams
-
Prepares data so it is fit for analysis. Finds missing values and outliers before they distort a result.
Python tools, Exploration
Analytics, Product teams
-
Tests relationships and causation with regression. Draws conclusions the data can actually support.
Causal analysis, Exploration
Research, Data science teams
- Data science teams
- Analytics
- Research
- Product teams
Data Scientist
Frames the problem before reaching for a model. Checks the data and the assumptions behind every result.
Over 10,000 students trust LUNARTECH
LUNARTECH gives you the skills
to learn, build, create and lead.
Engineers
Understand systems all the way down. Build the ones others rely on.
Scientists
Understand what the data says. Build models that hold up.
Researchers
Understand the papers. Build on them, and take the work further.
The field
Anyone can use AI.
Anyone can use AI.
Few can engineer it. This is where that starts.
+340%growth in open roles requiring AI skills
Roles and pay
~35,000 open roles right now
Open roles: Built In, Greenhouse, LinkedIn.
Typical salaries: Glassdoor, Levels.fyi, Payscale, Indeed, Ravio, JobRise, U.S. BLS. Military: 2026 U.S. basic pay, drone officers with aviation incentive pay.
Updated November 2026.
FAQ
Frequently asked questions.
Need help? These answers cover most of what people ask before they start.
Pandas and NumPy for data manipulation, and Scikit-learn for machine learning.
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Yes. Our support remains strong both during your free trial and after you subscribe. Reach the team at info@lunartech.ai with any question, whether you’re onboarding, navigating your trial, or need help as a member. Subscribers to the yearly plan also receive dedicated support in one-on-one sessions.
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The case study
Take one project all the way through.
Two hours and five modules: one machine learning project, from problem to refined model. Begin with a free lesson, or enroll in the full course.
