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### 25 Complimentary Courses in Mastering Data Science, Data Engineering, Machine Learning, MLOps, and Generative AI

Discover a collection of top courses to launch your dream career or master a new skill, all for fre…

It is imperative to acquire expertise in data technology, machine learning, and artificial intelligence in today’s rapidly evolving scientific domain. Numerous online resources are accessible, many of which are cost-free, whether you are embarking on a new career path or enhancing your existing knowledge. To present you with a curated selection of exceptional programs, we have compiled the top recommendations for free courses from KDnuggets. It is advisable to bookmark this page for future reference as you may utilize it to explore new programs or acquire fresh skills.

Professor Charles Severance’s “Python for Everyone” offers a comprehensive introduction to programming using Python, ideal for novices.

  1. Delve into data analysis using Python with Jovian.
  2. Acquire skills in managing databases with SQL by accessing “Databases and SQL” from freeCodeCamp.
  3. Enhance your understanding of predictive analytics through the introductory course on interpretive data available on Upwork.
  4. Engage with Zoomcamp for Machine Learning by DataTalks Club, a practical, project-based approach to teaching machine learning.

Refer to “5 Free Courses to Master Data Science” for detailed insights into each program.

Master the fundamentals of data engineering with IBM on dsc.

  1. Navigate Google’s “Data Engineer Learning Path,” a guide for aspiring data professionals.
  2. Obtain certification in database engineering through the “Database Engineer Professional Certificate” from Meta.
  3. Explore big data technologies and applications in UC San Diego’s “Big Data Specialization.”
  4. Participate in DataTalks’ “The Data Engineering Zoomcamp Club,” a hands-on, project-oriented data engineering course.

Explore “5 Free Courses to Master Data Engineering” for in-depth information on each program.

Embark on Kaggle’s “Intro to Machine Learning,” a user-friendly introduction to machine learning.

  1. Discover Kylie Ying’s “Machine Learning for Everyone,” offering an accessible perspective on machine learning concepts.
  2. Focus on machine learning using Python and Scikit-Learn by FUNMOOC.
  3. Engage with Google’s machine learning crash course, a concise yet comprehensive primer on the subject.
  4. Enroll in Stanford University’s “CS229: Machine Learning” for a more advanced course to broaden your knowledge.

Consult “5 Free Courses to Master Machine Learning” for a comprehensive overview of each program.

Enroll in Duke University’s “Python Essentials for MLOps,” a vital training for enthusiasts.

  1. Start your journey with Udemy’s “MLOps for Beginners,” an excellent entry point for novices.
  2. Deep dive into machine learning engineering for production (MLOps) with DeepLearning’s specialization. AI.
  3. Focus on the managerial aspects of machine learning in Duke University’s “Machine Learning Operations Specialization.”
  4. Explore Goku Mohandas’ “Made With ML,” a unique program blending machine learning with real-world applications, highly popular on GitHub.

Refer to “5 Free Courses to Master MLOps” for detailed insights into each program.

Explore Microsoft’s “Generative AI for Beginners,” comprising 12 modules on creating conceptual AI applications.

  1. Gain insights into the fundamentals of relational AI with DataBricks’ Generative AI Elements.
  2. Dive into Google’s “Introduction to Generative AI Learning Path,” covering essential AI principles and large language models.
  3. Explore Big Language Models for Generative AI by AWS and DeepLearning. AI, offering practical AI experience in real-world business scenarios.
  4. Engage with DeepLearning’s “Generative AI for All AI,” focusing on the workings, applications, and limitations of Generative AI.

Refer to “5 Free Courses to Master Generative AI” for detailed information on each program.

In total, we have highlighted 25 free online courses that can aid in establishing a strong foundation in data science and its related domains. Consider pursuing advanced courses in areas such as machine learning, MLOps, and generative AI to refine your skills. These complimentary programs offer high-quality education accessible to all, irrespective of your stage in the data science learning journey. They provide adaptable learning options to suit even the busiest schedules. Best wishes on your learning endeavors!

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Last modified: December 28, 2023
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