Master Data Science 2025: Get Hired Fast, Build AI Skills & Drive Impact

This comprehensive roadmap from Data Science & AI expert Tatev Aslanyan delivers the fastest, most effective path to become job-ready in 2025.

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3
Hours
LUNARTECH
August 2025
Available online
Master Data Science 2025: Get Hired Fast, Build AI Skills & Drive Impact

In this course,
you'll learn

Launch Your Career Roadmap

Own a step-by-step roadmap and the key skills to launch your data science career in 2024

Master Foundational Skills

Master the math and stats foundations required for advanced ML and AI innovation

Build Real-World Models

Build, evaluate and deploy real-world models using Python, AB testing and NLP basics

Drive Business Decisions

Translate complex analyses into clear business insights that drive decisions and career growth

Tatev Aslanyan
Your instructor

Tatev Aslanyan

Tatev brings industry experience, advanced AI/ML degrees, and a reputation as a thought leader in data science to LunarTech. She holds Bachelors and Masters degrees in STEM. Her publications in top journals and presentations at international conferences showcase her expertise.

Trusted by over 10.000 students

Course program

Here's a glimpse of what you'll learn throughout the course

Module 1

Chapter 1: Welcome to Data Science in 2024

Instructor’s background and the course vision for rapid learning. Defining data science: data + math + stats + ML for business wins. How data science drives value and competitive advantage. Industry applications: healthcare, retail, finance, energy. Case studies: predictive patient outcomes, personalization, fraud detection, sustainability

Module 2

Chapter 2: Your Data Science Career Path & Outlook

Why ~85% of companies are hiring data scientists now. What to expect: impact, excitement, and real-world challenges. Common entry roles and career trajectories. Salary benchmarks and negotiation tips. Data science as the launchpad to AI & ML mastery

Module 3

Chapter 3: Foundational Mathematics for Data Science

High-school essentials: algebra, trig, geometry refresh. Differential theory: derivatives, gradients, integrals. Multivariate calculus: partial derivatives and optimization. Optimization algorithms: GD, SGD, momentum, RMSprop. Linear algebra: vectors, matrices, operations. Solving systems: Gaussian elimination & reduction. Eigenvalues, eigenvectors & decompositions. Vector spaces: span, basis, null space, Gram-Schmidt. QR decomposition, rank & dimensions. Going beyond libraries: math for true ML/AI insight

Module 4

Chapter 4: Mastering Statistics for Data-Driven Decisions

Random variables, populations vs. samples. Probability basics, conditional probability & Bayes’ rule. Descriptive stats: mean, variance, correlation, covariance. Key distributions: normal, Poisson, binomial. Inferential stats: regression for causal insight. Hypothesis testing: t-tests, F-tests, chi-square. Statistical significance: p-values & error types. Law of Large Numbers & Central Limit Theorem

Module 5

Chapter 5: Core Machine Learning Fundamentals

Supervised vs. unsupervised learning paradigms. Classification vs. regression models and use cases. ML workflow: training, validation, testing & splits. Linear & logistic regression deep dive. KNN & LDA for simple predictive tasks. Decision trees for classification and regression. Ensembles: bagging, boosting & random forests. Advanced boosters: XGBoost, AdaBoost, LightGBM. Resampling: k-fold, leave-one-out & bootstrapping. Predictive analytics with traditional ML. Regression metrics: MSE & RMSE. Classification metrics: cross‐entropy, F1, precision, recall

Module 6

Chapter 6: Practical Data Science: AB Testing & NLP Basics

AB testing fundamentals: design, metrics & pitfalls. Power analysis & sample-size calculation. Conducting tests: monitoring integrity & avoiding p-hacking. Analyzing results in Python: SE, variance, p-values. Interpreting significance vs. practical impact. Intro to NLP: tokenization, BoW, TF-IDF. Word embeddings & semantic analysis. Overview of LLMs: BERT, GPT-3/4, T5

Hear from Our Graduates

At LunarTech, we're proud of the successes of our students. Here's what some of them have to say

“LunarTech is gold. I wanted to learn machine learning as a beginner and LunarTech cleared my mind. After engaging with LunarTech's content, I have a clear vision and now I can proceed further on my own.”

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“At 38, the tech world felt like foreign territory until this course from LunarTech illuminated the path. In six months, I transitioned from an absolute beginner to receiving multiple job offers.”

Verified Twitter User

“LunarTech's course prepared me for real-world challenges, going beyond traditional learning methods. It instilled in me the confidence to pursue and attain a position at my dream company.”

Verified Youtube User

“Facing self-doubt, this course was a turning point. LunarTech's comprehensive curriculum and supportive community laid the groundwork for my transformation from a hopeful learner to a proficient.”

Verified Youtube User

“This course honed my abilities for the competitive job market, and I credit it with helping me ace my software engineer interviews and kickstart my career.”
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Why choose us

Focus on Your Success

LunarTech is invested in your goals, with personalized learning plans and support structures to help you overcome challenges.

Industry-Aligned Curriculum

Our courses are constantly updated to reflect the latest tools, techniques, and in-demand skills employers are seeking.

Hands-On Practice

Study on your schedule. SkillSprint is accessible 24/7, so you can learn at your pace, anytime, anywhere.

Flexible Learning

Study at your own pace, from anywhere and at any time, on your terms.

Certificate of Completion

Receive a SkillSprint certificate to showcase your new skills.

Lifetime Alumni Network

Even after graduation, stay connected to the LunarTech community for ongoing support, job opportunities, and industry insights.

Frequently asked questions

Need help? Check out our FAQ section for quick and easy solutions.

Is the investment in your Data Science Bootcamp really worth it?

Our data science bootcamp is designed to provide you with the most comprehensive and relevant curriculum available . Enroll now and you’ll get immediate access to valuable resources, including expert guidance from experienced professionals and a supportive community of like-minded learners.

Let’s do the math together:

Our bootcamps cost $149.97 for 30 days, $99.97 monthly for 180 day-plan Semi-Annually, $79.97 monthly for 365 day-plan Annual plan.

That breaks down to:

max $149.97/30 = $4.93 per day

mid $99.97/30 = $3.33 per day

min $79.97/30 = $2.67 per day

That’s less than the cost of a daily Starbucks coffee! And while coffee might give you a quick energy boost, our bootcamp will provide you with long-term knowledge and skills that can enhance your career opportunities. Don’t miss out on this cost-effective and valuable opportunity.

What does the free trial include?

Our 3-day free trial gives you access to selection of  content in bootcamp, courses and materials, designed for you to experience the value of our content firsthand. This includes comprehensive learning materials and interactive sessions. You won’t be charged during this period, though we require your credit card details at the start to ensure a seamless transition should you choose to continue with our service.

Will I need to enter my credit card details to start the free trial?

Yes, entering your credit card details is a necessary step to begin your free trial. This process is entirely secure, ensuring total privacy and safety of your information. We ask for this to provide a seamless transition to a paid subscription if you decide to continue beyond the free trial. You will only be charged after the trial period ends, granting you full access to our content based on the chosen subscription plan.

What happens after my free trial ends?

After your 3-day free trial, you’ll gain access to the full breadth of our content, contingent upon the subscription plan you choose. We offer free trials for our monthly, biannual, and annual plans. Each plan provides a different scope of access and benefits, ensuring that you find the perfect fit for your learning journey.

What should I do if my employer agrees to pay for my subscription?

If your employer has agreed to fund your learning journey, whether partially or in full, please contact us at tk.lunartech@gmail.com or info@lunartech.ai. We’ll work closely with you and your employer to set up everything needed for your subscription, ensuring a smooth and hassle-free process.

Is there support available if I have questions during my free trial or after subscribing?

Yes, our commitment to exceptional customer support remains strong both during your free trial and after you’ve subscribed. You can reach out to our support team via tk.lunartech@gmail.com or info.lunartech.ai for assistance with any questions or issues, whether you’re in the onboarding process, navigating your trial, or need help as a subscribing member. Plus, subscribers to our yearly plan receive dedicated support during their one-on-one sessions.

Can I change my plan later on?

Absolutely, you can upgrade your plan at any time during your subscription. However, downgrading is not available for bi-yearly or yearly; you can opt to cancel and then choose a new plan that better suits your needs. For those on biannual or annual plans, we offer the convenience of paying in installments, making it easier to manage payments, please reach out to us to learn more.

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