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Spend some quality time with Pluralsight Principal Author Simon Allardice as he skips right over all the same-old tired buzzword topics and helps uncover the not-so-obvious insights we've been missing.

Spend some quality time with Pluralsight Principal Author Simon Allardice as he skips right over all the same-old tired buzzword topics and helps uncover the not-so-obvious insights we've been missing.

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What's inside

Syllabus

What you think you know about GenAI—and why it’s wrong

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Explores AI and its impact, making it highly relevant to current industry trends
Taught by a recognized expert in artificial intelligence, ensuring quality instruction
Covers the latest trends and advancements in the field of AI
Requires no prior knowledge of AI, making it accessible to beginners
Course is multi-modal, offering a mix of videos, readings, and discussions
May not provide enough depth for learners with existing AI knowledge

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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 What You Think You Know About GenAI—and Why It’s Wrong with these activities:
Compile a library of GenAI resources
Expand your knowledge of GenAI by gathering and organizing a comprehensive collection of relevant resources.
Browse courses on Generative AI
Show steps
  • Identify and collect high-quality articles, tutorials, and documentation on GenAI
  • Categorize and organize the resources based on topic or relevance
  • Create a central repository or platform to store and share the resources
Write a blog post or article about GenAI
Expand your understanding and share your knowledge by creating and publishing content about GenAI.
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Show steps
  • Choose a specific topic or aspect of GenAI to write about
  • Research and gather information from reliable sources
  • Structure and organize your content in a logical and engaging manner
  • Write and edit your content
  • Publish and distribute your content
  • Promote and share your content with others
Experiment with different GenAI models and techniques
Strengthen your understanding by experimenting with various GenAI models and techniques.
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Show steps
  • Choose a specific GenAI model or technique to experiment with
  • Set up the necessary environment and tools
  • Implement the model or technique and train it on a dataset
  • Evaluate the performance of the model or technique
  • Refine and improve the model or technique based on evaluation results
Four other activities
Expand to see all activities and additional details
Show all seven activities
Explore advanced GenAI techniques
Enhance your skills by following tutorials and experimenting with advanced GenAI techniques.
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  • Identify specific advanced GenAI techniques that you want to explore
  • Find and follow high-quality tutorials or documentation on these techniques
  • Implement and test the techniques in your own projects or experiments
  • Evaluate the results and identify areas for improvement
Mentor junior GenAI learners
Solidify your understanding by mentoring others and sharing your knowledge in GenAI.
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Show steps
  • Identify opportunities to mentor junior GenAI learners
  • Share your knowledge and expertise with them
  • Provide support and guidance to help them succeed
  • Learn from their questions and perspectives
Develop a prototype Generative AI
Solidify your understanding of GenAI by building a prototype that demonstrates its capabilities.
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Show steps
  • Choose a specific application for your Generative AI
  • Research and understand the different techniques involved in Generative AI
  • Design and implement your prototype
  • Test and evaluate your prototype
  • Refine and improve your prototype based on testing results
Contribute to an open-source GenAI project
Deepen your understanding and make a meaningful contribution to the GenAI community by collaborating on open-source projects.
Browse courses on Generative AI
Show steps
  • Identify an open-source GenAI project that aligns with your interests
  • Join the project community and contribute in ways that suit your skills
  • Collaborate with other contributors and learn from their experiences
  • Share your knowledge and insights with the community

Career center

Learners who complete What You Think You Know About GenAI—and Why It’s Wrong will develop knowledge and skills that may be useful to these careers:
Data Analyst
Data Analysts collect, clean, and analyze data to identify trends, patterns, and other insights. They work with data scientists, business analysts, and other professionals to interpret data and make recommendations for action. Data Analysts also work with IT professionals to develop and implement data analysis tools and techniques. A course like \"What You Think You Know About GenAI—and Why It’s Wrong\" may be useful for Data Analysts because it can help build a foundation of knowledge about artificial intelligence and machine learning.
AI Architect
AI Architects design and build AI systems. They work with stakeholders to understand business needs and translate those needs into technical requirements. AI Architects also work with data scientists, machine learning engineers, and software engineers to develop and deploy AI systems. A course like \"What You Think You Know About GenAI—and Why It’s Wrong\" may be useful for AI Architects because it can help build a foundation of knowledge about artificial intelligence and machine learning.
Data Scientist
Data Scientists use data to solve business problems. They collect, clean, analyze, and interpret data to identify trends, patterns, and other insights. Data Scientists work with a variety of tools and technologies, including machine learning algorithms, data analytics software, and statistical modeling techniques. A course like \"What You Think You Know About GenAI—and Why It’s Wrong\" may be useful for Data Scientists because it can help build a foundation of knowledge about artificial intelligence and machine learning.
Machine Learning Engineer
Machine Learning Engineers develop and deploy machine learning models to solve real-world problems. They work with data scientists, software engineers, and other professionals to design, build, and maintain machine learning systems. A course like \"What You Think You Know About GenAI—and Why It’s Wrong\" may be useful for Machine Learning Engineers because it can help build a foundation of knowledge about artificial intelligence and machine learning.
AI Researcher
AI Researchers conduct research to advance the frontiers of artificial intelligence. They develop new algorithms, techniques, and applications for artificial intelligence. AI Researchers work in a variety of settings, including academia, industry, and government. A course like \"What You Think You Know About GenAI—and Why It’s Wrong\" may be useful for AI Researchers because it can help build a foundation of knowledge about artificial intelligence and machine learning.
AI Consultant
AI Consultants help organizations adopt and implement AI solutions. They work with clients to identify business needs, develop AI strategies, and select and deploy AI technologies. AI Consultants also help clients manage the ethical and social implications of AI. A course like \"What You Think You Know About GenAI—and Why It’s Wrong\" may be useful for AI Consultants because it can help build a foundation of knowledge about artificial intelligence and machine learning.
Director of AI Research
Directors of AI Research oversee teams of research scientists and engineers to advance the frontiers of artificial intelligence technology. They work to develop machine learning algorithms, data analytics techniques, and other innovative advancements that can be applied to a variety of real-world problems. A course like \"What You Think You Know About GenAI—and Why It’s Wrong\" may be useful for Directors of AI Research because it can help build a foundation of knowledge about artificial intelligence and machine learning.
Software Engineer
Software Engineers design, develop, and maintain software systems. They work with a variety of programming languages and technologies to build applications that meet the needs of users. Software Engineers work in a variety of industries, including technology, finance, healthcare, and manufacturing. A course like \"What You Think You Know About GenAI—and Why It’s Wrong\" may be useful for Software Engineers because it can help build a foundation of knowledge about artificial intelligence and machine learning.
Financial Analyst
Financial Analysts analyze financial data and trends to make investment recommendations. They work with clients to develop investment strategies, manage portfolios, and assess risk. Financial Analysts also work with companies to raise capital and provide financial advice. A course like \"What You Think You Know About GenAI—and Why It’s Wrong\" may be useful for Financial Analysts because it can help build a foundation of knowledge about artificial intelligence and machine learning.
Product Manager
Product Managers are responsible for the development and launch of new products and features. They work with engineers, designers, and marketers to bring products to market that meet the needs of users. Product Managers also work with customers to gather feedback and improve products over time. A course like \"What You Think You Know About GenAI—and Why It’s Wrong\" may be useful for Product Managers because it can help build a foundation of knowledge about artificial intelligence and machine learning.
Operations Manager
Operations Managers oversee the day-to-day operations of an organization. They work with staff to ensure that operations run smoothly and efficiently. Operations Managers also work with other departments to coordinate activities and ensure that the organization meets its goals. A course like \"What You Think You Know About GenAI—and Why It’s Wrong\" may be useful for Operations Managers because it can help build a foundation of knowledge about artificial intelligence and machine learning.
Business Analyst
Business Analysts identify and analyze business needs to improve organizational performance. They work with stakeholders to understand business processes, identify areas for improvement, and develop solutions. Business Analysts also work with IT professionals to implement solutions and measure results. A course like \"What You Think You Know About GenAI—and Why It’s Wrong\" may be useful for Business Analysts because it can help build a foundation of knowledge about artificial intelligence and machine learning.
Sales Manager
Sales Managers lead and manage sales teams to achieve sales targets. They work with sales representatives to develop sales strategies, motivate and train sales teams, and close deals. Sales Managers also work with customers to build relationships and identify sales opportunities. A course like \"What You Think You Know About GenAI—and Why It’s Wrong\" may be useful for Sales Managers because it can help build a foundation of knowledge about artificial intelligence and machine learning.
Project Manager
Project Managers lead and manage projects to achieve project goals. They work with project teams to develop project plans, budgets, and timelines. Project Managers also work with stakeholders to communicate project status and ensure that the project meets its objectives. A course like \"What You Think You Know About GenAI—and Why It’s Wrong\" may be useful for Project Managers because it can help build a foundation of knowledge about artificial intelligence and machine learning.
Marketing Manager
Marketing Managers develop and implement marketing campaigns to promote products and services. They work with creative teams, product managers, and sales teams to create marketing materials, launch campaigns, and track results. Marketing Managers also work with customers to gather feedback and improve marketing efforts over time. A course like \"What You Think You Know About GenAI—and Why It’s Wrong\" may be useful for Marketing Managers because it can help build a foundation of knowledge about artificial intelligence and machine learning.

Reading list

We've selected 12 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 What You Think You Know About GenAI—and Why It’s Wrong.
Provides a comprehensive overview of computer vision, including topics such as the different types of computer vision algorithms, the applications of computer vision, and the challenges of computer vision.
Provides a comprehensive overview of statistical learning, including topics such as the different types of statistical learning models, the applications of statistical learning, and the challenges of statistical learning.
Provides a comprehensive overview of deep learning for natural language processing, including topics such as the different types of deep learning models for NLP, the applications of deep learning for NLP, and the challenges of deep learning for NLP.
Provides a comprehensive overview of pattern recognition and machine learning, including topics such as the different types of pattern recognition and machine learning models, the applications of pattern recognition and machine learning, and the challenges of pattern recognition and machine learning.
Provides a comprehensive overview of machine learning from a probabilistic perspective, including topics such as the different types of probabilistic machine learning models, the applications of probabilistic machine learning, and the challenges of probabilistic machine learning.
Provides a comprehensive overview of deep learning, including topics such as the history of deep learning, the different types of deep learning models, and the applications of deep learning.
Provides a comprehensive overview of speech and language processing, including topics such as the different types of speech and language processing algorithms, the applications of speech and language processing, and the challenges of speech and language processing.
Provides a practical guide to machine learning with Scikit-Learn, Keras, and TensorFlow, including topics such as the different types of machine learning models, the applications of machine learning, and the challenges of machine learning.
Provides a practical guide to deep learning with Python, including topics such as the different types of deep learning models, the applications of deep learning, and the challenges of deep learning.
Provides a practical guide to machine learning in action, including topics such as the different types of machine learning models, the applications of machine learning, and the challenges of machine learning.
Explores the potential implications of AI for the future of humanity, including topics such as the singularity, the potential for AI to create a new form of intelligence, and the potential for AI to help us solve some of the world's most pressing problems.

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