In DevOps, we are constantly seeking ways to optimize workflows—from automating deployments to monitoring system performance. In today’s world, where “Data is Power”, this principle holds even truer for DevOps Engineers working in organizations focused on Big Data.
Analyzing operational metrics and system logs can reveal bottlenecks, help predict potential failures, and enable continuous improvement. That’s why DevOps Vietnam has curated a list of more than 50 free Data Science courses from multiple platforms—perfect for anyone eager to explore the fascinating intersection between DevOps and Data Science.
Contents
Why Data Science Skills Matter for DevOps Engineers
While Data Science is often seen as a standalone career path, the truth is that many of its skills and tools are highly relevant to DevOps professionals. The ability to process and analyze large volumes of data empowers DevOps engineers to:
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Detect anomalies in infrastructure performance.
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Automate alerts and intelligent monitoring.
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Optimize resource usage across distributed systems.
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Drive evidence-based decision-making for deployments and scaling.
Beyond the DevOps context, to become a Data Scientist, you should develop proficiency in the following areas:
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Mathematics & Statistics
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Probability theory, descriptive and inferential statistics.
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Linear algebra and calculus for data modeling.
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Programming Skills
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Python, R, and SQL for data processing and analysis.
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Data Processing & Cleaning
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Handling missing values, outlier detection, data normalization.
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Machine Learning & Deep Learning
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Supervised, unsupervised, and reinforcement learning.
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Neural networks and advanced architectures.
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Big Data Technologies
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Hadoop, Spark, Kafka, and distributed processing.
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Data Visualization
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Tools like Matplotlib, Tableau, and Power BI.
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Deployment & MLOps
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Cloud-based model deployment with Docker and Kubernetes.
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Analytical & Problem-Solving Skills
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Breaking down complex issues using a data-driven approach.
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Soft Skills & Communication
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Presenting insights effectively to both technical and non-technical audiences.
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Many of these competencies overlap with those outlined in DevOps Vietnam’s free eBook: “Practical Roadmap to Becoming a DevOps Engineer”, making the learning journey more efficient for those transitioning between the two domains.
Curated List of 50+ Free Data Science Courses (Updated August 10, 2025)
Our research team has compiled this up-to-date list so you can quickly filter and choose the most relevant courses for your learning path.
| # | Course Title | Rating | Platform | Duration | Level |
|---|---|---|---|---|---|
| 1 | Data Science Full Program by Edureka | NA | YouTube | 10 hours | Beginner |
| 2 | Data Science Tutorial by Great Learning | NA | YouTube | 11 hours | Beginner |
| 3 | Data Science Full Course For Beginners | NA | YouTube | NA | Beginner |
| 4 | Learn Data Science Tutorial – Full Course for Beginners | NA | YouTube | 6 hours | Beginner |
| 5 | Data Science Full Course by Simplilearn | NA | YouTube | 10 hours | Beginner |
| 6 | Python for Data Science | NA | YouTube | 12 hours | Beginner |
| 7 | Statistics and Probability Full Course | NA | YouTube | 11 hours | Beginner |
| 8 | R Basics – R Programming Language Introduction | 4.6/5 | Udemy | 4h 6m | Beginner |
| 9 | Introduction to Data Science using Python (Module 1/3) | 4.5/5 | Udemy | 2h 32m | Beginner |
| 10 | What is Data Science? | 4.3/5 | Udemy | 40m | Beginner |
| 11 | Python For Data Science | 4.5/5 | Udemy | 3h 55m | Beginner |
| 12 | Learn NumPy Fundamentals | 4.7/5 | Udemy | 1h 49m | Beginner |
| 13 | Python for Data Science – Great Learning | 4.5/5 | Udemy | 1h 55m | Beginner |
| 14 | Intro to Data for Data Science | 4.5/5 | Udemy | 1h 1m | Beginner |
| 15 | Data Science, Machine Learning, Data Analysis, Python & R | 4.1/5 | Udemy | 8h 7m | Beginner |
| 16 | Data Science with Analogies, Algorithms, and Solved Problems | 4.2/5 | Udemy | 1h 19m | Beginner |
| 17 | Learn Data Science With R | 4.0/5 | Udemy | 8h 42m | Beginner |
| 18 | NumPy for Data Science Beginners: 2025 | 4.3/5 | Udemy | 1h 51m | Beginner |
| 19 | A–Z™ Python Crash Course for Data Science 2025 | 4.1/5 | Udemy | 2h | Beginner |
| 20 | SQL Crash Course for Aspiring Data Scientist | 4.2/5 | Udemy | 1h 24m | Beginner |
| 21 | SQL for Data Analysis: Solving Real-World Problems with Data | 4.4/5 | Udemy | 1h 57m | Beginner |
| 22 | Explore, Track, Predict the ISS in Real-Time with Python | 4.6/5 | Udemy | 1h 13m | Intermediate |
| 23 | Statistics | 4.7/5 | Udacity | 4 Months | Beginner |
| 24 | Intro to Data Analysis | 4.6/5 | Udacity | 6 Weeks | Beginner |
| 25 | Intro to Data Science | 4.7/5 | Udacity | 2 Months | Intermediate |
| 26 | Data Analysis and Visualization | 4.7/5 | Udacity | 16 Weeks | Intermediate |
| 27 | Data Visualization and D3.js | 4.7/5 | Udacity | 7 Weeks | Intermediate |
| 28 | Data Analysis with R | 4.6/5 | Udacity | 2 Months | Intermediate |
| 29 | Spark | 4.5/5 | Udacity | 10 Hours | Intermediate |
| 30 | Data Wrangling with MongoDB | 4.7/5 | Udacity | 2 Months | Intermediate |
| 31 | Real-Time Analytics with Apache Storm | 4.7/5 | Udacity | 2 Weeks | Intermediate |
| 32 | Linear Algebra Refresher Course with Python | 4.7/5 | Udacity | 4 Months | Intermediate |
| 33 | Model Building and Validation | 4.7/5 | Udacity | 8 Weeks | Advanced |
| 34 | Foundations of Data Science: K-Means Clustering in Python | 4.6/5 | Coursera | 29 Hours | Beginner |
| 35 | Machine Learning by Stanford University | 4.9/5 | Coursera | 60 Hours | Beginner |
| 36 | Data Analytics for Lean Six Sigma | 4.8/5 | Coursera | 11 Hours | Beginner |
| 37 | Probability and Statistics | 4.6/5 | Coursera | 16 Hours | Beginner |
| 38 | Data Science Ethics | 5/5 | Coursera | 15 Hours | Beginner |
| 39 | An Intuitive Introduction to Probability | 4.8/5 | Coursera | 30 Hours | Beginner |
| 40 | Data Science in Stratified Healthcare and Precision Medicine | 4.6/5 | Coursera | 17 Hours | Intermediate |
| 41 | Bayesian Statistics: From Concept to Data Analysis | 4.6/5 | Coursera | 12 Hours | Intermediate |
| 42 | Practical Time Series Analysis | 4.6/5 | Coursera | 26 Hours | Intermediate |
| 43 | Improving Your Statistical Inferences | 4.9/5 | Coursera | 28 Hours | Intermediate |
| 44 | Hands-on Text Mining and Analytics | 4.5/5 | Coursera | 13 Hours | Intermediate |
| 45 | Population Health: Predictive Analytics | 4.6/5 | Coursera | 18 Hours | Intermediate |
| 46 | Data Visualization | NA | Kaggle | 4 Hours | Beginner |
| 47 | Pandas | NA | Kaggle | 4 Hours | Beginner |
| 48 | Data Cleaning | NA | Kaggle | 4 Hours | Intermediate |
| 49 | Feature Engineering | NA | Kaggle | 6 Hours | Intermediate |
| 50 | Data Science: R Basics | NA | edX | 8 Weeks | Beginner |
| 51 | Learning from Data | NA | Caltech | 18 Hours | Intermediate |
Final Thoughts
With the explosion of data and the rapid evolution of technology, Data Science has become one of the most exciting and in-demand fields today. These free courses are not just a starting point—they can help you build a solid foundation and open doors to future career opportunities.
Whether you are a DevOps Engineer aiming to integrate advanced analytics into your workflows, or an aspiring Data Scientist charting your professional path, this curated collection is a powerful resource to get you started in 2025.
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