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Google Cloud Training

בקורס הזה נלמד על Generative AI Studio, מוצר ב-Vertex AI שעוזר ליצור אבות טיפוס למודלים של בינה מלאכותית גנרטיבית, כדי להשתמש בהם ולהתאים אותם לפי הצרכים שלכם. באמצעות הדגמה של המוצר עצמו, נלמד מהו Generative AI Studio, מהם הפיצ'רים והאפשרויות שלו, ואיך להשתמש בו. בסוף הקורס יהיה שיעור Lab מעשי לתרגול של מה שנלמד, ובוחן לבדיקת הידע.

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Syllabus

מבוא ל-Generative AI Studio
בקורס הזה נלמד על Generative AI Studio, מוצר ב-Vertex AI שעוזר ליצור אבות טיפוס למודלים של בינה מלאכותית גנרטיבית, כדי להשתמש בהם ולהתאים אותם לפי הצרכים שלכם. באמצעות הדגמה של המוצר עצמו, נלמד מהו Generative AI Studio, מהם הפיצ'רים והאפשרויות שלו, ואיך להשתמש בו. בסוף הקורס יהיה שיעור Lab מעשי לתרגול של מה שנלמד, ובוחן לבדיקת הידע.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Can be used as a building block for more advanced generative AI topics
Develops expertise in generative AI, which is an advanced topic in computer science
Provides a hands-on lab for practical experience
Requires some background knowledge in generative AI
May require additional software or tools not readily available
Instructors are Google Cloud Training, who are recognized for their work in generative AI

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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 Introduction to Generative AI Studio - בעברית with these activities:
Review Generative AI fundamentals
Strengthen your foundation by reviewing the basics of Generative AI before starting the course.
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  • Access online resources or textbooks on Generative AI.
  • Focus on understanding the concepts of generative models, GANs, and VAEs.
  • Complete practice exercises or quizzes to reinforce your knowledge.
Participate in Generative AI Studio study groups
Deepen your understanding by collaborating with peers in Generative AI Studio study groups.
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  • Join or create a study group focused on Generative AI Studio.
  • Meet regularly to discuss course materials, work on projects, and share insights.
  • Provide feedback and support to your fellow group members.
Review Statistics Refresher
Review the basics of statistics before the course to build a stronger foundation of concepts.
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  • Review descriptive statistics (mean, median, mode, variance, standard deviation).
  • Review basic probability concepts (Bayes Theorem, conditional probability).
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Follow a tutorial on using Generative AI Studio
Following a tutorial can help you quickly get started with Generative AI Studio and learn the basics of Generative AI.
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  • Find a tutorial on using Generative AI Studio
  • Follow the steps in the tutorial
  • Experiment with the different features of Generative AI Studio
Read Deep Learning with Python
Reading a book on deep learning with Python will help you understand the theoretical foundations of artificial intelligence and develop practical skills that enhance your ability to design, implement, and evaluate machine learning models.
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  • Read the book
Practice writing code in Python
Writing code is a fundamental aspect of deep learning. Regular coding practice helps you master the syntax and improves your ability to apply deep learning techniques in real-world scenarios.
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  • Set up a Python environment
  • Find coding exercises or projects
  • Write and test your code
Explore Generative AI Studio community resources
Expand your knowledge by exploring online forums and tutorials related to Generative AI Studio.
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  • Join Generative AI Studio online communities.
  • Search for tutorials and discussions related to your areas of interest.
  • Engage with other users and experts to ask questions and share insights.
Explore Machine Learning Jupyter Notebooks
Follow guided tutorials to gain hands-on experience with machine learning techniques.
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  • Identify reputable sources that provide Jupyter notebooks for machine learning.
  • Select a notebook that aligns with a topic covered in the course.
  • Go through the notebook step-by-step, understanding the code and its implementation.
Practice creating Generative AI models with Generative AI Studio
Practice creating Generative AI models to strengthen your understanding of the Generative AI Studio platform and the concepts of Generative AI.
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  • Review the documentation for Generative AI Studio
  • Create a new project in Vertex AI
  • Create a new dataset to store your training data
  • Use Generative AI Studio to create a Generative AI model
  • Train your model using the training data
Follow tutorials on generative AI
Following tutorials allows you to learn about specific applications and use cases of generative AI. This practical experience enriches your understanding and enables you to explore different dimensions of the technology.
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  • Discover relevant tutorials
  • Complete the tutorials
Complete Generative AI Studio tutorials
Reinforce your understanding of Generative AI Studio's features by working through practical tutorials.
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  • Access the Generative AI Studio documentation.
  • Select a tutorial that aligns with your learning objectives.
  • Follow the instructions and complete the exercises.
Solve Machine Learning Coding Exercises
Practice coding exercises to enhance problem-solving skills and solidify machine learning concepts.
Show steps
  • Find online coding platforms or textbooks with machine learning exercises.
  • Attempt to solve exercises independently, focusing on understanding the code structure.
  • Review solutions and learn from alternative approaches.
Build a presentation on Generative AI Studio
Creating a presentation helps you consolidate your knowledge and develop your presentation skills. By explaining Generative AI Studio to others, you reinforce your understanding of its features and capabilities.
Show steps
  • Summarize the key concepts
  • Design the presentation slides
  • Rehearse your presentation
Attend industry meetups and conferences
Networking events are a valuable platform to connect with professionals in the field. They provide opportunities to learn about industry trends, exchange ideas, and explore potential collaborations related to generative AI.
Show steps
  • Identify relevant events
  • Register and attend
Attend Machine Learning Meetups or Conferences
Engage with professionals to learn best practices and expand knowledge of machine learning.
Show steps
  • Identify local or virtual machine learning meetups or conferences.
  • Attend events, participate in discussions, and network with professionals.
Join a study group or online forum dedicated to Generative AI Studio
Joining a study group or online forum can provide you with opportunities to connect with other learners, ask questions, and share knowledge.
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  • Find a study group or online forum dedicated to Generative AI Studio
  • Introduce yourself to the group
  • Participate in discussions and ask questions
  • Help other members of the group
Contribute to open-source projects related to generative AI
Contributing to open-source projects provides hands-on experience in applying generative AI techniques. It helps you enhance your technical skills and gain a deeper understanding of the practical applications of this technology.
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  • Find a suitable project
  • Set up a development environment
  • Implement changes or fix issues
Create a Generative AI Studio app
Develop your own Generative AI Studio application to solidify your understanding of the product's features and capabilities.
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  • Choose a project idea that aligns with your interests and goals.
  • Gather the necessary resources and tools.
  • Follow the Generative AI Studio documentation to build your app.
  • Deploy your app and share it with others.
Mentor junior developers in generative AI
Mentoring others not only benefits the mentee but also reinforces your understanding of generative AI. By sharing your knowledge and expertise, you deepen your own comprehension and make a valuable contribution to the community.
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  • Identify a mentee
  • Establish a mentoring relationship
Design a Generative AI Studio workflow
Enhance your problem-solving skills by designing a comprehensive Generative AI Studio workflow.
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  • Identify a business problem that can be solved with Generative AI Studio.
  • Design a workflow that utilizes Generative AI Studio's features.
  • Create a presentation or document that outlines your workflow.
Annotated Machine Learning Bibliography
Create a resource compilation to provide deeper knowledge and expand topics covered during the course.
Show steps
  • Collect academic papers, articles, and blog posts related to machine learning.
  • Organize sources into categories (e.g., algorithms, techniques, applications).
  • Annotate each source with a summary, key takeaways, and personal insights.
Connect with a Machine Learning Mentor
Seek guidance from experienced individuals in the field to accelerate learning and development.
Show steps
  • Identify potential mentors through professional networks or online platforms.
  • Reach out to mentors and express interest in guidance on machine learning.
  • Establish regular communication and seek advice on technical concepts, career paths, and industry trends.
Build a Machine Learning Model for a Real-World Problem
Apply machine learning skills to a real-world problem, solidifying understanding and developing practical experience.
Show steps
  • Identify a problem or dataset that can be addressed using machine learning.
  • Clean and prepare the data.
  • Select and train a machine learning model.
  • Evaluate the model's performance.
  • Deploy the model and track its performance in a production environment.
Write a blog post about your experience using Generative AI Studio
Writing a blog post about your experience with Generative AI Studio can help you consolidate your knowledge and share your learnings with others.
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  • Choose a topic for your blog post
  • Write an outline for your blog post
  • Write the content for your blog post
  • Edit and proofread your blog post
  • Publish your blog post
Participate in Generative AI Studio challenges
Test your skills and push your limits by participating in Generative AI Studio challenges.
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  • Identify Generative AI Studio challenges that align with your interests.
  • Form a team or work individually on the challenge.
  • Develop and submit your solution.
  • Evaluate your results and learn from the experience.
Participate in Machine Learning Hackathons or Challenges
Challenge problem-solving abilities and gain exposure to diverse machine learning domains.
Show steps
  • Search for hackathons or challenges that focus on machine learning.
  • Team up or work independently to develop innovative machine learning solutions.
  • Submit your solution and present it to judges if shortlisted.

Career center

Learners who complete Introduction to Generative AI Studio - בעברית will develop knowledge and skills that may be useful to these careers:
AI Engineer
AI Engineers are responsible for designing, building, and maintaining AI systems. They work with a variety of AI technologies, including machine learning, natural language processing, and computer vision. AI Engineers may use Generative AI Studio to create prototypes of generative AI models to test and validate their ideas. The course can help AI Engineers build a foundation in generative AI and learn how to apply it to real-world problems.
Machine Learning Engineer
Machine Learning Engineers are responsible for developing and deploying machine learning models. They work with data scientists to identify the right models for a given problem, they build and optimize AI models using data, and they deploy and monitor models to ensure they are running smoothly. Generative AI Studio can help Machine Learning Engineers build and train generative AI models, such as text generators, image generators, and music generators. By learning how to use this platform, Machine Learning Engineers can expand their skillset and become more valuable to their organizations.
Software Engineer
Software Engineers are responsible for designing, developing, and maintaining software applications. They work with a variety of programming languages and technologies to create software that meets the needs of users. Software Engineers who want to specialize in generative AI may find Generative AI Studio to be a useful tool. By learning how to use this platform, Software Engineers can build and train generative AI models, such as text generators, image generators, and music generators. This can help them create more innovative and engaging software applications.
Data Analyst
Data Analysts are responsible for collecting, cleaning, and analyzing data to help businesses make informed decisions. They use a variety of statistical and data visualization techniques to identify trends and patterns in data. Generative AI Studio may be a useful tool for Data Analysts who want to explore the potential of generative AI. By learning how to use this platform, Data Analysts can build and train generative AI models to generate new data or augment existing data sets. This can help them gain deeper insights into their data and make more accurate predictions.
Data Scientist
Data Scientists are responsible for collecting, cleaning, and analyzing data to help businesses make informed decisions. They use a variety of statistical and machine learning techniques to identify trends and patterns in data. The skills taught in Generative AI Studio, such as understanding how to use and interpret generative AI models, may be useful for Data Scientists who want to apply generative AI to their work. By enhancing their skills with this course, Data Scientists can stay up-to-date on the latest advances in generative AI and use it to create innovative solutions for their organizations.
Product Manager
Product Managers are responsible for defining and managing the development of products. They work with a variety of stakeholders, including engineers, designers, and marketers, to ensure that products meet the needs of users. Product Managers who want to incorporate generative AI into their products may find Generative AI Studio to be a valuable tool. By learning how to use this platform, Product Managers can build and train generative AI models that can generate text, images, or music. This can help them create more innovative and engaging products.
Marketing Manager
Marketing Managers are responsible for developing and executing marketing campaigns. They work with a variety of teams, including sales, product, and engineering, to create and implement marketing strategies. Marketing Managers who want to incorporate generative AI into their campaigns may find Generative AI Studio to be a valuable tool. By learning how to use this platform, Marketing Managers can build and train generative AI models that can generate text, images, or music. This can help them create more engaging and effective marketing campaigns.
UX Designer
UX Designers are responsible for designing the user experience of websites and applications. They work with engineers and designers to create interfaces that are intuitive, easy to use, and visually appealing. UX Designers who want to learn more about generative AI may find Generative AI Studio to be a useful tool. By learning how to use this platform, UX Designers can build and train generative AI models that can generate text, images, or music. This can help them create more innovative and engaging user experiences.
Business Analyst
Business Analysts are responsible for analyzing business processes and identifying opportunities for improvement. They work with a variety of stakeholders, including executives, managers, and employees, to gather data and develop recommendations. Business Analysts who want to learn more about generative AI may find Generative AI Studio to be a useful tool. By learning how to use this platform, Business Analysts can build and train generative AI models that can generate text, images, or music. This can help them create more innovative and effective solutions to business problems.
Quantitative Analyst
Quantitative Analysts are responsible for developing and implementing mathematical models to analyze financial data. They work with a variety of data sources, including market data, financial statements, and economic data, to identify investment opportunities. Quantitative Analysts who want to learn more about generative AI may find Generative AI Studio to be a useful tool. By learning how to use this platform, Quantitative Analysts can build and train generative AI models that can generate text, images, or music. This can help them create more innovative and effective quantitative models.
Actuary
Actuaries are responsible for assessing and managing financial risks. They work with a variety of data sources, including insurance data, mortality data, and economic data, to develop and implement risk management strategies. Actuaries who want to learn more about generative AI may find Generative AI Studio to be a useful tool. By learning how to use this platform, Actuaries can build and train generative AI models that can generate text, images, or music. This can help them create more innovative and effective risk management strategies.
Operations Research Analyst
Operations Research Analysts are responsible for developing and implementing mathematical models to solve business problems. They work with a variety of data sources, including financial data, operational data, and customer data, to identify opportunities for improvement. Operations Research Analysts who want to learn more about generative AI may find Generative AI Studio to be a useful tool. By learning how to use this platform, Operations Research Analysts can build and train generative AI models that can generate text, images, or music. This can help them create more innovative and effective solutions to business problems.

Reading list

We've selected seven 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 Introduction to Generative AI Studio - בעברית.
Provides a practical guide to using generative AI for web development, covering topics such as how to generate images, text, and audio for your website.
Provides a comprehensive overview of deep learning, covering a wide range of topics, including convolutional neural networks, recurrent neural networks, and transformers.
Provides a thought-provoking exploration of the potential of generative AI, discussing the impact that generative AI is likely to have on society and the economy.
Provides a comprehensive overview of machine learning, covering a wide range of topics, including supervised learning, unsupervised learning, and reinforcement learning.

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