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Noah Gift,
Alfredo Deza,
and
Derek Wales
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.
Register for this course and see more details by visiting:
OpenCourser.com/course/1tapvx/databricks
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What's inside
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.
Read more
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.
Read more
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.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Covers Responsible Generative AI, which is standard in industry
Taught by Noah Gift, Alfredo Deza, Derek Wales, who are recognized for their work in the topic that the course teaches
Explores Local LLMOps, which is highly relevant in an academic setting
Explores Data Transformation and Pipelines, which is highly relevant to industry
Examines Databricks Lakehouse Platform Fundamentals, which is standard in industry
Save this course
Save Databricks to Local LLMs to your list so you can find it easily later:
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Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Databricks to Local LLMs with these
activities:
Review Python programming basics
Show steps
Brush up on Python programming basics to strengthen your foundation for data engineering and data analytics.
Browse courses on
Python
Show steps
-
Review Python syntax and data types
-
Practice writing Python programs
Review linear algebra and statistics concepts
Show steps
Refresh your knowledge of linear algebra and statistics concepts to enhance your understanding of data analytics.
Browse courses on
Linear Algebra
Show steps
-
Review the key concepts of linear algebra
-
Review the key concepts of statistics
-
Practice solving linear algebra and statistics problems
Create a glossary of key Databricks and LLM terms
Show steps
Compile a glossary of key Databricks and LLM terms to improve your understanding of the core concepts.
Show steps
-
Review the Databricks documentation and LLM documentation
-
Identify the key terms and concepts
-
Create a glossary of terms with definitions
Five other activities
Expand to see all activities and additional details
Show all eight activities
Attend a Databricks workshop to learn about best practices
Show steps
Attend a Databricks workshop to gain hands-on experience and learn best practices for using the Databricks platform.
Show steps
-
Find an upcoming Databricks workshop
-
Register for the workshop and attend all sessions
-
Participate in hands-on exercises and ask questions
Participate in a study group to discuss course topics
Show steps
Join a study group to discuss course topics and reinforce your understanding.
Show steps
-
Find a study group or create your own
-
Meet regularly to discuss course topics
-
Share your knowledge and learn from others
Build a data lakehouse using Databricks
Show steps
Build a data lakehouse using Databricks to gain a practical understanding of the Databricks Lakehouse Platform and its capabilities.
Show steps
-
Create a new cluster and notebook in Databricks
-
Load data into your data lakehouse
-
Run queries on your data
-
Create a data pipeline to transform your data
-
Deploy your data application
Deploy a local large language model using Hugging Face
Show steps
Deploy a local large language model using Hugging Face to gain experience with deploying and using LLMs.
Browse courses on
Local LLMOps
Show steps
-
Install Hugging Face and set up your environment
-
Load a pre-trained LLM from Hugging Face
-
Fine-tune the LLM on your own dataset
-
Deploy your LLM as a web service
-
Evaluate the performance of your LLM
Contribute to the Hugging Face community
Show steps
Contribute to the Hugging Face community to gain hands-on experience with open source development and LLM applications.
Browse courses on
Hugging Face
Show steps
-
Find a project to contribute to
-
Contribute code or documentation to the project
-
Participate in community discussions
Review Python programming basics
Show steps
Brush up on Python programming basics to strengthen your foundation for data engineering and data analytics.
Browse courses on
Python
Show steps
Show steps
Show steps
- Review Python syntax and data types
- Practice writing Python programs
Review linear algebra and statistics concepts
Show steps
Refresh your knowledge of linear algebra and statistics concepts to enhance your understanding of data analytics.
Browse courses on
Linear Algebra
Show steps
Show steps
Show steps
- Review the key concepts of linear algebra
- Review the key concepts of statistics
- Practice solving linear algebra and statistics problems
Create a glossary of key Databricks and LLM terms
Show steps
Compile a glossary of key Databricks and LLM terms to improve your understanding of the core concepts.
Show steps
Show steps
Show steps
- Review the Databricks documentation and LLM documentation
- Identify the key terms and concepts
- Create a glossary of terms with definitions
Five other activities
Expand to see all activities and additional details
Show all eight activities
Attend a Databricks workshop to learn about best practices
Show steps
Attend a Databricks workshop to gain hands-on experience and learn best practices for using the Databricks platform.
Show steps
Show steps
Show steps
- Find an upcoming Databricks workshop
- Register for the workshop and attend all sessions
- Participate in hands-on exercises and ask questions
Participate in a study group to discuss course topics
Show steps
Join a study group to discuss course topics and reinforce your understanding.
Show steps
Show steps
Show steps
- Find a study group or create your own
- Meet regularly to discuss course topics
- Share your knowledge and learn from others
Build a data lakehouse using Databricks
Show steps
Build a data lakehouse using Databricks to gain a practical understanding of the Databricks Lakehouse Platform and its capabilities.
Show steps
Show steps
Show steps
- Create a new cluster and notebook in Databricks
- Load data into your data lakehouse
- Run queries on your data
- Create a data pipeline to transform your data
- Deploy your data application
Deploy a local large language model using Hugging Face
Show steps
Deploy a local large language model using Hugging Face to gain experience with deploying and using LLMs.
Browse courses on
Local LLMOps
Show steps
Show steps
Show steps
- Install Hugging Face and set up your environment
- Load a pre-trained LLM from Hugging Face
- Fine-tune the LLM on your own dataset
- Deploy your LLM as a web service
- Evaluate the performance of your LLM
Contribute to the Hugging Face community
Show steps
Contribute to the Hugging Face community to gain hands-on experience with open source development and LLM applications.
Browse courses on
Hugging Face
Show steps
Show steps
Show steps
- Find a project to contribute to
- Contribute code or documentation to the project
- Participate in community discussions
Career center
Learners who complete Databricks to Local LLMs will develop knowledge and skills
that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers build and deploy machine learning models. This course will help you to learn how to use Databricks to perform data engineering and data analytics tasks for data science workflows. You will also learn how to master running local large language models like Mixtral via Hugging Face Candle and Mozilla llamafile.
Data Analyst
Data Analyst
Data Analysts use data to make informed decisions. This course will help you to learn how to use Databricks to perform data engineering and data analytics tasks. You will learn how to describe the Databricks architecture, create clusters, use notebooks for analysis, and share notebooks. The course will also cover responsible generative AI, which is an important consideration for data analysts who are working with sensitive data.
Data Engineer
Data Engineer
Data Engineers maintain and transform large and complex sets of data. This course will help you to understand the fundamentals of the Databricks Lakehouse Platform, which is a popular platform for data engineering. You will learn how to read and transform data, create Delta Lake pipelines, and work with complex data types. The course will also cover responsible generative AI, which is an important consideration for data engineers who are working with sensitive data.
Data Scientist
Data Scientist
Data Scientists use data to solve business problems. This course will help you to learn how to use Databricks to perform data engineering and data analytics tasks for data science workflows. You will also learn how to master running local large language models like Mixtral via Hugging Face Candle and Mozilla llamafile.
Financial Analyst
Financial Analyst
Financial Analysts use data to make investment decisions. This course will help you to learn how to use Databricks to perform data engineering and data analytics tasks. You will also learn how to master running local large language models like Mixtral via Hugging Face Candle and Mozilla llamafile.
Marketing Analyst
Marketing Analyst
Marketing Analysts use data to understand customer behavior and improve marketing campaigns. This course will help you to learn how to use Databricks to perform data engineering and data analytics tasks. You will also learn how to master running local large language models like Mixtral via Hugging Face Candle and Mozilla llamafile.
Risk Analyst
Risk Analyst
Risk Analysts use data to identify and assess risks. This course will help you to learn how to use Databricks to perform data engineering and data analytics tasks. You will also learn how to master running local large language models like Mixtral via Hugging Face Candle and Mozilla llamafile.
Product Manager
Product Manager
Product Managers develop and manage products. This course will help you to learn how to use Databricks to perform data engineering and data analytics tasks. You will also learn how to master running local large language models like Mixtral via Hugging Face Candle and Mozilla llamafile.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze financial data. This course will help you to learn how to use Databricks to perform data engineering and data analytics tasks. You will also learn how to master running local large language models like Mixtral via Hugging Face Candle and Mozilla llamafile.
Data Governance Analyst
Data Governance Analyst
Data Governance Analysts develop and implement data governance policies. This course will help you to learn how to use Databricks to perform data engineering and data analytics tasks. You will also learn how to master running local large language models like Mixtral via Hugging Face Candle and Mozilla llamafile.
Sales Analyst
Sales Analyst
Sales Analysts use data to improve sales performance. This course will help you to learn how to use Databricks to perform data engineering and data analytics tasks. You will also learn how to master running local large language models like Mixtral via Hugging Face Candle and Mozilla llamafile.
Data Management Analyst
Data Management Analyst
Data Management Analysts design and implement data management systems. This course will help you to learn how to use Databricks to perform data engineering and data analytics tasks. You will also learn how to master running local large language models like Mixtral via Hugging Face Candle and Mozilla llamafile.
Business Analyst
Business Analyst
Business Analysts use data to improve business processes. This course will help you to learn how to use Databricks to perform data engineering and data analytics tasks. You will also learn how to master running local large language models like Mixtral via Hugging Face Candle and Mozilla llamafile.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use data to improve the efficiency and effectiveness of organizations. This course will help you to learn how to use Databricks to perform data engineering and data analytics tasks. You will also learn how to master running local large language models like Mixtral via Hugging Face Candle and Mozilla llamafile.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. This course will help you to learn how to use Databricks to perform data engineering and data analytics tasks. You will also learn how to master running local large language models like Mixtral via Hugging Face Candle and Mozilla llamafile.
For more career information including salaries, visit:
OpenCourser.com/course/1tapvx/databricks
Reading list
We've selected eight books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Databricks to Local LLMs.
Explores the ethical challenges of AI, including the problem of AI alignment. It valuable resource for anyone who wants to learn more about the ethical implications of AI.
Save
Explores the potential risks and benefits of superintelligence. It valuable resource for anyone who wants to learn more about the future of AI.
Save
Explores the history and future of AI, including the potential of AI to solve some of the world's biggest problems. It valuable resource for anyone who wants to learn more about the potential of AI.
Save
Comprehensive textbook on deep learning. It covers everything from the basics of deep learning to the latest advances in the field. It valuable resource for anyone who wants to learn more about deep learning.
Comprehensive textbook on reinforcement learning. It covers everything from the basics of reinforcement learning to the latest advances in the field. It valuable resource for anyone who wants to learn more about reinforcement learning.
Save
Explores the potential future of humanity, including the role of AI in shaping our future. It valuable resource for anyone who wants to learn more about the future of humanity.
Save
Explores the potential impact of AI on society, including the challenges and opportunities that AI presents. It valuable resource for anyone who wants to learn more about the impact of AI on society.
Explores the ethical and social implications of AI, including the potential impact of AI on our jobs, our privacy, and our democracy. It valuable resource for anyone who wants to learn more about the ethical and social implications of AI.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/1tapvx/databricks
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Effort
5 hours a work a week of study for a total of 20 hours
Level
Introductory
Via
Coursera
Institution
Duke University
Instructors
Noah Gift
Alfredo Deza
Derek Wales
Language
English
Transcripts
Español
Français
Português
Deutsch
Italiano
中文
العربية
한국어
日本語
हिंदी
Nederlands
Svenska
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This course belongs to a
collection
called
Large Language Model Operations (LLMOps). It's comprised of five courses:
- Databricks to Local LLMs (viewing)
- Open Source LLMOps Solutions
- Operationalizing LLMs on Azure
- GenAI and LLMs on AWS
- Advanced Data Engineering
Good to know
Covers Responsible Generative AI, which is standard in industry
Taught by Noah Gift, Alfredo Deza, Derek Wales, who are recognized for their work in the topic that the course teaches
Explores Local LLMOps, which is highly relevant in an academic setting
Explores Data Transformation and Pipelines, which is highly relevant to industry
Examines Databricks Lakehouse Platform Fundamentals, which is standard in industry
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