The Data Science Course: Complete Data Science Bootcamp
by 365 Careers · Udemy
Our Verdict
Worth it — with caveats365 Careers' Data Science Course is the best foundational survey on Udemy for absolute beginners, but it is a strong starting point rather than a job-ready bootcamp. It is one of the platform's most popular all-in-one entry points, holding a 4.6/5 rating across roughly 160,000 ratings (Class Central). Its real differentiator is breadth plus an unusually solid theoretical foundation: it walks complete beginners through probability, descriptive and inferential statistics, and linear algebra before reaching Python, machine learning, and deep learning with TensorFlow 2.0. Reviewers consistently say it 'teaches you to think like a data scientist' rather than just copy code, and it is frequently on sale for $10-15, making the value hard to beat. The honest trade-offs are real, though: each topic is covered more shallowly than a dedicated course would (365's own platform spends 173 hours on the same path versus this 32-hour bundle), SQL and production/MLOps deployment are thin despite the 'data to deployment' framing, and there are no real portfolio projects, peer feedback, or career services. It is an excellent foundation, not a job-ready bootcamp on its own.
Strong, well-priced foundational survey for true beginners who want statistics and Python intuition before specializing, but the breadth-over-depth design, lack of substantial hands-on projects, and thin SQL/deployment coverage mean it should be a starting point paired with project work and a deeper specialization, not a standalone path to a data science job.
Best for: Complete beginners and career changers from non-technical backgrounds who want a single affordable course that builds genuine intuition for the math and statistics behind data science before touching Python, machine learning, and deep learning. It suits self-directed learners who value understanding 'why' over speed and want a structured tour of the whole field to decide where to specialize next.
Skip if: People who already know Python and statistics and want depth in a specific area (advanced ML, NLP, MLOps), anyone expecting a project-heavy, job-ready portfolio bootcamp with mentorship or career services, and those needing strong SQL, big data tooling, or modern model-deployment workflows, all of which are light here.
About This Course
Covers math, statistics, Python, ML, deep learning, and TensorFlow for a full data science workflow from data to deployment.
What You'll Learn
Curriculum
Foundational concepts and terminology linking traditional data, business intelligence, analytics, machine learning, and AI.
Distributions, combinatorics, and Bayesian inference as the statistical groundwork.
Descriptive and inferential statistics, including hypothesis testing.
Python basics from data types and syntax through functions, OOP, and core libraries.
Linear and logistic regression, cluster analysis, and K-means clustering applied in Python.
Vectors, matrices, and linear algebra that support machine learning and deep learning.
Neural networks and convolutional neural networks built with TensorFlow 2.0.
Real-world application including data preprocessing and business analysis with Tableau.
Prerequisites
- No prior programming or data science experience required; the course starts from absolute basics
- Comfort with high-school-level math is helpful since the course builds up probability, statistics, and linear algebra from the ground up
- Self-discipline for ~32 hours of self-paced video plus quizzes and coding exercises
Instructor
365 Careers
Instructor · Udemy
Pros & Cons
Pros
- Unusually strong math and statistics foundation for an introductory course; reviewers say it teaches you to think like a data scientist rather than just paste code
- Genuinely beginner-friendly and self-contained, taking learners with zero technical background from probability through deep learning in one structured path
- Excellent value, with a list price around $120 but frequent Udemy sales to roughly $10-15 plus a 30-day money-back guarantee
- Includes quizzes and coding exercises throughout, and a single 4.6/5 rating sustained across roughly 160,000 ratings signals consistent learner satisfaction
- Modern toolchain for an intro bundle: Python, NumPy, pandas, scikit-learn, TensorFlow 2.0, and Tableau
Cons
- Breadth over depth: every topic is treated more lightly than a dedicated course would; the same provider's standalone platform spends 173 hours on this material versus 32 hours here
- Light on real portfolio projects, peer feedback, and career services, so it is not job-ready on its own and must be paired with independent project work
- SQL and modern production/MLOps deployment are thin despite the 'data to deployment' positioning
- Some learners criticize the voiceover as flat or robotic, which can make longer stretches harder to stay engaged with
Alternatives To Consider
Frequently Asked Questions
Is The Data Science Course: Complete Data Science Bootcamp free?
The Data Science Course: Complete Data Science Bootcamp is $12.99. List price ~$120 but routinely discounted on Udemy to roughly $10-15 (catalog shows $12.99); includes a certificate of completion and a 30-day money-back guarantee. No free audit option.
Who is The Data Science Course: Complete Data Science Bootcamp for?
Complete beginners and career changers from non-technical backgrounds who want a single affordable course that builds genuine intuition for the math and statistics behind data science before touching Python, machine learning, and deep learning. It suits self-directed learners who value understanding 'why' over speed and want a structured tour of the whole field to decide where to specialize next.
What will you learn in The Data Science Course: Complete Data Science Bootcamp?
Foundations of data science: how data, business intelligence, analytics, machine learning, and AI relate; Probability and statistics: distributions, combinatorics, Bayesian inference, descriptive and inferential statistics, and hypothesis testing; Python programming from scratch, including core syntax, functions, OOP, and the NumPy, pandas, and scikit-learn libraries; Machine learning with linear and logistic regression, cluster analysis, and K-means clustering using real datasets.
What are the prerequisites for The Data Science Course: Complete Data Science Bootcamp?
No prior programming or data science experience required; the course starts from absolute basics; Comfort with high-school-level math is helpful since the course builds up probability, statistics, and linear algebra from the ground up; Self-discipline for ~32 hours of self-paced video plus quizzes and coding exercises.
Is The Data Science Course: Complete Data Science Bootcamp worth it?
Strong, well-priced foundational survey for true beginners who want statistics and Python intuition before specializing, but the breadth-over-depth design, lack of substantial hands-on projects, and thin SQL/deployment coverage mean it should be a starting point paired with project work and a deeper specialization, not a standalone path to a data science job.
How we reviewed this course
This is an independent editorial assessment by Cursarium, based on Udemy's published course materials and aggregated public learner feedback (last reviewed 2026-06). We have not independently completed the course. Links to providers are standard references, not paid placements.
Sources
- Class Central - The Data Science Course (rating and listing)
- Reddemy - Reddit sentiment aggregation for the course
- Technoven - Udemy Data Science Course Review (curriculum and metrics)
- Javarevisited - Is the Data Science Bootcamp worth it review
- Skill Frontier - 365 Data Science vs Udemy depth comparison