As part of the GenAI Academy, this course explores how Generative Artificial Intelligence (GenAI) is transforming the field of data engineering. This course serves as a primer where learners will discover the key capabilities of GenAI and uncover practical strategies to leverage these powerful tools in their day-to-day data engineering work.
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As part of the GenAI Academy, this course explores how Generative Artificial Intelligence (GenAI) is transforming the field of data engineering. This course serves as a primer where learners will discover the key capabilities of GenAI and uncover practical strategies to leverage these powerful tools in their day-to-day data engineering work.
As part of the GenAI Academy, this course explores how Generative Artificial Intelligence (GenAI) is transforming the field of data engineering. This course serves as a primer where learners will discover the key capabilities of GenAI and uncover practical strategies to leverage these powerful tools in their day-to-day data engineering work.
This course is designed for data engineering team leaders and data engineers, including managers and team leads who are responsible for guiding their teams towards innovative practices, as well as data engineers and aspiring professionals looking to enhance their workflows and future-proof their skillsets by incorporating GenAI-powered tools.
Learners should have a basic understanding of data pipelines, ETL/ELT processes, and data transformation, along with familiarity with databases, data warehouses, big data frameworks, and programming languages like Python and SQL. An open mindset and curiosity to explore new GenAI technologies are essential.
By the end of this course, data engineers will be equipped with the knowledge and skills to start scaling their productivity by harnessing the transformative potential of GenAI.
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Activities
Review data engineering fundamentals
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Refresh your understanding of core data engineering principles to enhance your comprehension of GenAI's capabilities.
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Data Pipelines
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Review online articles and tutorials on data pipelines, ETL/ELT processes, and data transformation.
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Revisit past course materials or textbooks on these topics.
Data Engineering Toolkit
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Gather and organize resources, tools, and notes related to GenAI and data engineering to support your learning journey.
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GenAI
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Identify relevant online resources, such as articles, tutorials, and documentation
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Download and organize these materials in a centralized location
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Summarize key concepts and create cheat sheets for quick reference
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Review the materials regularly to reinforce your understanding
Data Visualization Tutorials
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Explore online tutorials to familiarize yourself with techniques for visualizing data using GenAI tools.
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GenAI
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Identify platforms offering data visualization tutorials
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Research and select tutorials relevant to GenAI
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Follow the tutorials, taking notes and practicing the techniques
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Apply the techniques to visualize your own data
Six other activities
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GenAI Collaborative Discussion
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Engage in discussions with peers, sharing knowledge, experiences, and insights related to GenAI and data engineering.
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GenAI
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Find a peer group or online forum focused on GenAI
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Participate in discussions and ask questions related to course topics
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Share your own knowledge and help others understand
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Reflect on the discussions and apply the insights to your own work
Use Python to manipulate and analyze data
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Get hands-on experience applying GenAI tools in Python to analyze real-world datasets, solidifying your understanding of GenAI capabilities.
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Data Manipulation
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Find a public dataset
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Write a Python script
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Analyze the results
Personal Data Generation Project
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Apply your GenAI skills to a practical project, creating a data generation tool that meets your specific needs.
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GenAI
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Identify a domain or problem where data generation is needed
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Design the data generation pipeline using GenAI tools
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Implement and test the pipeline
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Evaluate the generated data and refine the pipeline as necessary
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Document and share your findings
Practice GenAI model training
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Develop proficiency in training GenAI models to enhance your understanding of model capabilities and limitations.
Browse courses on
Generative AI
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Follow guided tutorials or workshops on training GenAI models using text, image, or audio data.
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Train models using different algorithms, hyperparameters, and datasets.
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Evaluate the results, identify patterns, and optimize the models for improved performance.
Generative AI Model Testing
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Enhance your understanding of Generative AI models by testing their performance on various tasks and datasets.
Browse courses on
GenAI
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-
Choose a Generative AI model and dataset
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Design and conduct experiments to test the model's performance
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Analyze the results and identify areas for improvement
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Refine and iterate the model based on the findings
GenAI Hackathon
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Challenge yourself by participating in a GenAI hackathon, applying your skills to solve real-world problems.
Browse courses on
GenAI
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-
Identify a GenAI hackathon that aligns with your interests
-
Form a team or work individually on a project
-
Brainstorm and develop a solution using GenAI tools
-
Present your solution and compete for recognition
Review data engineering fundamentals
Show steps
Refresh your understanding of core data engineering principles to enhance your comprehension of GenAI's capabilities.
Browse courses on
Data Pipelines
Show steps
- Review online articles and tutorials on data pipelines, ETL/ELT processes, and data transformation.
- Revisit past course materials or textbooks on these topics.
Data Engineering Toolkit
Show steps
Gather and organize resources, tools, and notes related to GenAI and data engineering to support your learning journey.
Browse courses on
GenAI
Show steps
- Identify relevant online resources, such as articles, tutorials, and documentation
- Download and organize these materials in a centralized location
- Summarize key concepts and create cheat sheets for quick reference
- Review the materials regularly to reinforce your understanding
Data Visualization Tutorials
Show steps
Explore online tutorials to familiarize yourself with techniques for visualizing data using GenAI tools.
Browse courses on
GenAI
Show steps
- Identify platforms offering data visualization tutorials
- Research and select tutorials relevant to GenAI
- Follow the tutorials, taking notes and practicing the techniques
- Apply the techniques to visualize your own data
GenAI Collaborative Discussion
Show steps
Engage in discussions with peers, sharing knowledge, experiences, and insights related to GenAI and data engineering.
Browse courses on
GenAI
Show steps
- Find a peer group or online forum focused on GenAI
- Participate in discussions and ask questions related to course topics
- Share your own knowledge and help others understand
- Reflect on the discussions and apply the insights to your own work
Use Python to manipulate and analyze data
Show steps
Get hands-on experience applying GenAI tools in Python to analyze real-world datasets, solidifying your understanding of GenAI capabilities.
Browse courses on
Data Manipulation
Show steps
- Find a public dataset
- Write a Python script
- Analyze the results
Personal Data Generation Project
Show steps
Apply your GenAI skills to a practical project, creating a data generation tool that meets your specific needs.
Browse courses on
GenAI
Show steps
- Identify a domain or problem where data generation is needed
- Design the data generation pipeline using GenAI tools
- Implement and test the pipeline
- Evaluate the generated data and refine the pipeline as necessary
- Document and share your findings
Practice GenAI model training
Show steps
Develop proficiency in training GenAI models to enhance your understanding of model capabilities and limitations.
Browse courses on
Generative AI
Show steps
- Follow guided tutorials or workshops on training GenAI models using text, image, or audio data.
- Train models using different algorithms, hyperparameters, and datasets.
- Evaluate the results, identify patterns, and optimize the models for improved performance.
Generative AI Model Testing
Show steps
Enhance your understanding of Generative AI models by testing their performance on various tasks and datasets.
Browse courses on
GenAI
Show steps
- Choose a Generative AI model and dataset
- Design and conduct experiments to test the model's performance
- Analyze the results and identify areas for improvement
- Refine and iterate the model based on the findings
GenAI Hackathon
Show steps
Challenge yourself by participating in a GenAI hackathon, applying your skills to solve real-world problems.
Browse courses on
GenAI
Show steps
- Identify a GenAI hackathon that aligns with your interests
- Form a team or work individually on a project
- Brainstorm and develop a solution using GenAI tools
- Present your solution and compete for recognition
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