Coursera

Databricks to Local LLMs (Coursera)

Offered by Duke University,

By the end of this course, a learner will master Databricks to perform data engineering and data analytics tasks for data science workflows. Additionally, a student will learn to master running local large language models like Mixtral via Hugging Face Candle and Mozilla llamafile.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

What you'll learn

Databricks
ML pipelines
llamafile and other local LLMs like Mixtral

Syllabus

Databricks Lakehouse Platform Fundamentals
This week, you will learn how to describe the Databricks architecture, create clusters, use notebooks for analysis, and share notebooks by completing hands-on labs and knowledge checks on these topics.

Data Transformation and Pipelines
This week, you will learn how to read and transform data, create Delta Lake pipelines, and work with complex data types by implementing ETL solutions and passing code samples reviews.

Responsible Generative AI
This week you will learn foundations of generative AI and responsible deployment strategies to benefit from the latest advancements while maintaining safety, accuracy, and oversight. By directly applying concepts through hands-on labs and peer discussions, you will gain practical experience putting AI into production.

Local LLMOps
This week, you will learn mitigation strategies, evaluate task performance, and operationalize workflows by identifying risks in notebooks and deploying an LLM application.

Go to Class

MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Coursera

IBM

IBM Data Topology (Coursera)

CS: Information & Technology

Every business and organization is facing new challenges with their data. Pressures related to regulation and compliance, leveraging AI, spanning multicloud environments, and increasing volumes of inaccessible data are forcing executives and administrators to either modernize their infrastructures or become obsolete.

Aug 17th 2026

1 Week

Artificial Intelligence Data Management Data Science

Coursera

IBM

Machine Learning Introduction for Everyone (Coursera)

Data Science

This three-module course introduces machine learning and data science for everyone with a foundational understanding of machine learning models. You’ll learn about the history of machine learning, applications of machine learning, the machine learning model lifecycle, and tools for machine learning. You’ll also learn about supervised versus unsupervised learning, classification, regression, evaluating machine learning models, and more.

Aug 17th 2026

3 Weeks

ML Artificial Intelligence Machine Learning

Coursera

Politecnico di Milano

Technologies and platforms for Artificial Intelligence (Coursera)

Robotics & Computer Vision

This course will address the hardware technologies for machine and deep learning (from the units of an Internet-of-Things system to a large-scale data centers) and will explore the families of machine and deep learning platforms (libraries and frameworks) for the design and development of smart applications and systems.

Aug 17th 2026

4 Weeks

Artificial Intelligence Cloud Machine Learning

Coursera

DeepLearning.AI

Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning (Coursera)

CS: Software Engineering Computer Science

If you are a software developer who wants to build scalable AI-powered algorithms, you need to understand how to use the tools to build them. This course is part of the upcoming Machine Learning in Tensorflow Specialization and will teach you best practices for using TensorFlow, a popular open-source framework for machine learning.

Aug 17th 2026

4 Weeks

Artificial Intelligence Machine Learning Neural Networks

Coursera

University of Michigan

Applied Machine Learning in Python (Coursera)

Statistics & Data Analysis Data Science

This course will introduce the learner to applied machine learning, focusing more on the techniques and methods than on the statistics behind these methods. The course will start with a discussion of how machine learning is different than descriptive statistics, and introduce the scikit learn toolkit through a tutorial.

Aug 17th 2026

4 Weeks

Python ML Machine Learning

Coursera

Google Cloud

Introduction to Image Generation (Coursera)

CS: Information & Technology

This course introduces diffusion models, a family of machine learning models that recently showed promise in the image generation space. Diffusion models draw inspiration from physics, specifically thermodynamics. Within the last few years, diffusion models became popular in both research and industry. Diffusion models underpin many state-of-the-art image generation models and tools on Google Cloud. This course introduces you to the theory behind diffusion models and how to train and deploy them on Vertex AI.

Aug 17th 2026

3 Weeks

Machine Learning Coursera Plus Image Generation

Coursera

FIA Business School

Cadeia de Suprimentos na Nuvem (Coursera)

Business

Nossas boas-vindas ao Curso Cadeia de Suprimentos na Nuvem. Neste curso, você aprenderá como o supply chain pode ampliar o valor da empresa explorando as diversas ferramentas disponíveis em cloud para potencializar a visibilidade e a responsividade da cadeia, melhorando o nível de serviço prestado aos clientes.

Aug 17th 2026

5-12 Weeks

Cloud Machine Learning Big Data

Coursera

Coursera Instructor Network

Leveraging Virtual Assistants for Personal Productivity (Coursera)

Data Science

In a fast-paced world, managing personal productivity is crucial. This course introduces beginners to the world of virtual assistants and chatbots and how they can be harnessed to enhance personal productivity. Learn how to use these AI-driven tools effectively to streamline tasks, manage time, and boost overall efficiency.

Aug 17th 2026

1 Week

Artificial Intelligence Productivity Time Management

Coursera

University of Washington,Microsoft

Designing Autonomous AI (Coursera)

Data Science

When children learn how to hit a baseball, they don’t start with fastballs. Their coaches begin with the basics: how to grip the handle of the bat, where to put their feet and how to keep their eyes on the ball. Similarly, an autonomous AI system needs a subject matter expert (SME) to break a complex process or problem into easier tasks that give the AI important clues about how to find a solution faster.

Aug 17th 2026

4 Weeks

Artificial Intelligence AI Coursera Plus

Coursera

New York University Tandon School of Engineering

Fundamentals of Machine Learning in Finance (Coursera)

Data Science

The course aims at helping students to be able to solve practical ML-amenable problems that they may encounter in real life that include: (1) understanding where the problem one faces lands on a general landscape of available ML methods, (2) understanding which particular ML approach(es) would be most appropriate for resolving the problem, and (3) ability to successfully implement a solution, and assess its performance.

Aug 17th 2026

4 Weeks

Finance Machine Learning Clustering

Coursera

Coursera Instructor Network

Building Production-Ready Apps with Large Language Models (Coursera)

Data Science

In the age of artificial intelligence (AI), it is essential to learn how to apply the power of large language models (LLMs) for building various production-ready applications. In this hands-on-course, learners will gain the necessary skills for building and responsibly deploying a conversational AI application.

Aug 17th 2026

1 Week

Python Artificial Intelligence AI

Coursera

Politecnico di Milano

Ethics of Artificial Intelligence (Coursera)

Robotics & Computer Vision

This course deals with the problems created, aggravated or transformed by AI. It is intended to give students a chance to reflect on the ethical, social, and cultural impact of AI by focusing on the issues faced by and brought about by professionals in AI but also by citizens, institutions and societies. The course addresses these topics by means of case studies and examples analyzed in the light of the main ethical frameworks.

Aug 17th 2026

4 Weeks

Artificial Intelligence Ethics AI