DeepSeek & Generative AI Masterclass for Software engineers from Udemy

Unlock the full potential of DeepSeek with our comprehensive course, designed to guide you from foundational concepts to advanced applications in Artificial Intelligence (AI), Machine Learning (ML), Deep Learning, and Generative AI.

Course Overview:

Foundations of AI and ML: Begin your journey by understanding the core principles of AI and ML, setting a solid groundwork for more complex topics.
Deep Learning and Generative AI: Delve into the intricacies of deep learning, exploring neural networks and their applications. Uncover the evolution and mechanics of generative AI, understanding how models like DeepSeek are revolutionizing content creation and problem-solving.
Advanced AI Topics: Expand your knowledge with advanced subjects such as Reinforcement Learning, Tokenization, Temperature Scaling, Embeddings, and Foundation Models. Gain insights into the training methodologies of generative AI models and dissect the Transformer architecture that powers them.
Hands-On DeepSeek Prompting: Transition from theory to practice with hands-on sessions focused on DeepSeek prompting. Learn to craft prompts ranging from basic to advanced levels, enhancing your skills in software development life cycle (SDLC) processes and career advancement.
DeepSeek Internals and Architecture: Explore the technical marvel that is DeepSeek. Study its architecture in detail, including innovative techniques like Mixture of Experts, Multi-Head Latent Attention, Multi-Token Prediction, Distillation, Chain-of-Thought (CoT), Group Relative Policy Optimization (GRPO), and FP8. These lectures are enriched with insights from leading AI research papers.
Programmatic Access to DeepSeek: Learn how to integrate DeepSeek into your projects programmatically. Gain proficiency in accessing DeepSeek through APIs, utilizing platforms like Amazon Bedrock and LM studio. Engage with practical examples and compare API costs with services like OpenAI's ChatGPT, understanding DeepSeek's cost-effective advantages.

Why Choose This Course?

Comprehensive Curriculum: From basics to advanced topics, this course covers all essential aspects of DeepSeek and its applications in AI.
Practical Application: Engage in hands-on exercises that bridge the gap between theoretical knowledge and real-world application.
Expert Insights: Learn from content derived from cutting-edge AI research, ensuring you receive up-to-date and relevant information.
Cost Efficiency: Understand how DeepSeek offers a competitive edge with its cost-effective solutions compared to other AI models.

Don't miss this opportunity to elevate your understanding of DeepSeek and Generative AI. Enroll now to unlock a world of hands-on examples, in-depth architectural insights, and practical knowledge on implementing this groundbreaking AI technology.

What's inside

Learning objectives

Artificial intelligence : basics of ai. key concepts of ai, ai/ml differences, deep learning. real life examples of ai, ml, deep learning and generative ai.
Generative ai internals : gpt (generative pre-trained transformer), gen ai timeline, democratization of ai
Deepseek : effective prompts to improve productivity. build career - create resume and prepare for interview. 1000+ prompts with practical examples
Deepseek internals and deepseek architecture
Deepseek benchmark comparison, multi-head latent attention (mla), mixture-of-experts (moe), auxiliary-loss-free strategy, and multi-token prediction

Deepseek post training : reinforcement learning, supervised learning, chain-of-thought (cot), distillation
Deepseek : programmatically access deepseek apis, with aws bedrock, lm studio
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Artificial intelligence : basics of ai. key concepts of ai, ai/ml differences, deep learning. real life examples of ai, ml, deep learning and generative ai.
Generative ai internals : gpt (generative pre-trained transformer), gen ai timeline, democratization of ai
Deepseek : effective prompts to improve productivity. build career - create resume and prepare for interview. 1000+ prompts with practical examples
Deepseek internals and deepseek architecture
Deepseek benchmark comparison, multi-head latent attention (mla), mixture-of-experts (moe), auxiliary-loss-free strategy, and multi-token prediction
Deepseek post training : reinforcement learning, supervised learning, chain-of-thought (cot), distillation
Deepseek : programmatically access deepseek apis, with aws bedrock, lm studio
Show more
Show less

Syllabus

Intro to AI/ML & Generative AI - Watch at 1.5x if you already know these well

Introduction to Artificial Intelligence and it's real-life applications

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Covers the transformer architecture, which is a core component of modern deep learning and natural language processing systems

Explores the software development lifecycle (SDLC) processes, which helps learners apply AI tools to their existing workflows

Includes hands-on sessions focused on DeepSeek prompting, which allows learners to immediately apply their knowledge

Examines the Mixture of Experts (MoE) architecture, which is a cutting-edge technique for scaling up large language models

Requires learners to programmatically access DeepSeek APIs, which may require familiarity with cloud computing platforms

Compares DeepSeek API costs with OpenAI's ChatGPT, which helps learners understand the economic trade-offs of different AI models

Reviews summary

Practical deepseek & generative ai for engineers

According to learners, this course provides a practical and hands-on deep dive into DeepSeek and Generative AI, specifically tailored for software engineers. Students appreciate the coverage of DeepSeek internals and architecture, noting it goes beyond basic prompting. The hands-on sections, particularly those focusing on prompting techniques and API access via Bedrock and LM Studio, are highlighted as highly useful. While some felt the initial AI/ML theory parts could be reviewed quickly if already familiar, the core content on DeepSeek's unique features and practical application for tasks like resume building and project work is considered a major strength.

Initial sections can be quick; DeepSeek parts are detailed.

"The initial intro to AI/ML part is quite fast-paced, but the DeepSeek specific sections slow down nicely."

"I recommend watching the intro sections at 1.5x speed if you have prior AI knowledge, as suggested."

"The DeepSeek architecture and internals sections were dense but well-explained."

"The pacing felt right for the technical DeepSeek content, maybe a bit fast initially."

Explains complex architecture & training methods.

"The course did a great job explaining concepts like MLA, MTP, and CoT in the DeepSeek architecture."

"Understanding the training methodologies like Reinforcement Learning and Distillation was very insightful."

"It goes into detail on topics often glossed over in other courses."

"The explanations of the Transformer architecture and foundational models were clear and useful."

Content is highly relevant for software engineers.

"This masterclass is perfect for software engineers wanting to leverage Gen AI effectively in their workflow."

"The sections on coding, testing, and end-to-end projects are directly relevant to my job."

"Using DeepSeek for resume building and interview prep is a fantastic, practical use case covered."

"As a software engineer, I found the technical depth and practical focus spot on."

Concentrates deeply on DeepSeek's features.

"I was looking for something beyond just general Gen AI, and this course dives specifically into DeepSeek's unique aspects."

"Finally a course that explains DeepSeek's architecture like MoE and MLA."

"Understanding DeepSeek's internals gave me a competitive edge compared to just using ChatGPT."

"The focus on DeepSeek is excellent, covering its benchmarks and architecture in detail."

Offers valuable hands-on prompting and API labs.

"The hands-on prompting levels (Level 0 to Level 6) were incredibly helpful for practical application."

"Learning to access DeepSeek programmatically through Bedrock and LM Studio was exactly what I needed for my projects."

"Loved the practical examples and coding exercises, they solidify the concepts."

"The API access sections are very practical and directly applicable to my work."

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 DeepSeek & Generative AI Masterclass for Software engineers with these activities:

Review Foundational AI/ML Concepts

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Reinforce your understanding of fundamental AI and ML concepts to better grasp the advanced topics covered in the course.

Browse courses on Artificial Intelligence

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Review basic AI and ML definitions.
Summarize the differences between AI, ML, and Deep Learning.
Identify real-world applications of each.

Read 'Deep Learning' by Goodfellow, Bengio, and Courville

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Deepen your understanding of the theoretical underpinnings of deep learning and generative AI.

View Deep Learning on Amazon

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Focus on chapters related to generative models and transformers.
Work through the mathematical derivations and proofs.
Relate the concepts to DeepSeek's architecture and training methods.

Read 'Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow'

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Gain a deeper understanding of the machine learning landscape and the tools used to build AI models.

View Hands-On Machine Learning with Scikit-Learn,... on Amazon

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Read the chapters on neural networks and deep learning.
Experiment with the code examples provided in the book.
Relate the concepts to DeepSeek's architecture and functionality.

Four other activities

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Experiment with DeepSeek API parameters

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Master the DeepSeek API by systematically experimenting with different parameters and observing their effects.

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Obtain API access through Openrouter.ai or Amazon Bedrock.
Write a script to call the DeepSeek API with varying parameters.
Analyze the output and document the impact of each parameter.

Create a DeepSeek Prompt Engineering Guide

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Solidify your understanding of DeepSeek prompting by creating a comprehensive guide for other users.

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Document various prompting techniques learned in the course.
Provide examples of effective prompts for different tasks.
Explain the limitations of DeepSeek prompting.
Share your guide with the course community.

Fine-tune a Generative Model

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Apply your knowledge of generative AI by fine-tuning a pre-trained model on a specific dataset.

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Select a pre-trained generative model (e.g., GPT-2).
Choose a dataset relevant to your interests.
Fine-tune the model using a framework like TensorFlow or PyTorch.
Evaluate the performance of the fine-tuned model.

Contribute to a DeepSeek-related Open Source Project

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Enhance your skills and contribute to the community by participating in an open-source project related to DeepSeek.

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Find an open-source project that utilizes DeepSeek.
Identify a bug or feature to work on.
Submit a pull request with your changes.

Career center

Learners who complete DeepSeek & Generative AI Masterclass for Software engineers will develop knowledge and skills that may be useful to these careers:

Prompt Engineer

Prompt Engineers craft effective prompts for large language models to generate desired outputs. This course places a strong emphasis on hands-on DeepSeek prompting. It focuses on crafting prompts ranging from basic to advanced levels. It helps enhance skills applicable to software development life cycle processes and career advancement. By learning the intricacies of DeepSeek and how to programmatically access it, these engineers may gain a competitive edge. This course is particularly relevant for anyone aiming to master the art and science of prompt engineering.

See salaries and explore the career path for Prompt Engineer

Generative AI Specialist

A Generative AI Specialist focuses on developing and implementing generative AI models for content creation. This course delves into the evolution and mechanics of Generative AI, which may equip specialists with essential knowledge. The exploration of DeepSeek prompting can provide practical skills in crafting effective prompts. Understanding the technicalities of DeepSeek, including its architecture and innovative techniques, can help Generative AI Specialists optimize model performance. The course's practical examples and insights from leading AI research may prove invaluable. This is a great opportunity for Generative AI specialists.

See salaries and explore the career path for Generative AI Specialist

Machine Learning Engineer

A Machine Learning Engineer develops and deploys machine learning models. This course provides a foundation in AI and ML, which is essential for any machine learning engineer. It explores deep learning and generative AI. The course's focus on DeepSeek internals and architecture, including Mixture of Experts and Multi-Head Latent Attention, may provide a deeper understanding of model design and optimization. Furthermore, the hands-on sessions on DeepSeek prompting helps build practical skills in model interaction and refinement. Machine Learning Engineers may find this course specifically beneficial.

See salaries and explore the career path for Machine Learning Engineer

AI Application Developer

An AI Application Developer builds and implements AI-powered applications. This course helps you understand the foundations of AI and Machine Learning. It could further assist in exploring the intricacies of Deep Learning and Generative AI, which are vital for creating intelligent applications. The study of DeepSeek prompting may aid developers in integrating and optimizing AI models for real-world use. The course's coverage of programmatic access to DeepSeek, including APIs and platforms like Amazon Bedrock, can provide the skills needed to deploy AI applications effectively. For those looking to integrate AI into software solutions, this course may be invaluable.

See salaries and explore the career path for AI Application Developer

AI Research Scientist

An AI Research Scientist conducts research to advance the field of artificial intelligence. This course helps cover the foundations of AI and ML, and delves into Deep Learning and Generative AI. More importantly, the course explores DeepSeek internals and architecture, including techniques like Mixture of Experts and Multi-Head Latent Attention. This exploration is enriched with insights from leading AI research papers. The course can provide the theoretical and practical knowledge needed to contribute to AI research, making it valuable for aspiring AI Research Scientists, especially those interested in generative models.

See salaries and explore the career path for AI Research Scientist

Computational Linguist

A Computational Linguist develops computational models of natural language. This course may prove particularly useful. It includes a solid grounding in AI and ML concepts. The course's exploration of Deep Learning and Generative AI may help computational linguists understand the latest advancements in natural language processing. The hands-on DeepSeek prompting sessions could offer practical insights into how language models can be used and refined. This course may be useful for a Computational Linguist.

See salaries and explore the career path for Computational Linguist

AI Consultant

An AI Consultant advises organizations on how to implement AI solutions. This course helps establish a foundation in AI and ML and further advances knowledge in Deep Learning and Generative AI. The consultant may benefit from the practical skills gained through DeepSeek prompting sessions and hands-on examples. The consultant will be prepared to offer informed guidance to organizations looking to leverage generative AI technologies, especially DeepSeek. The AI consultant career role fits this course well.

See salaries and explore the career path for AI Consultant

Data Scientist

A Data Scientist analyzes data and uses machine learning techniques to derive insights. This course introduces the core principles of AI and ML, which helps provide a solid groundwork for data analysis and model building. The course includes the study of Deep Learning, Generative AI, and advanced AI topics like Reinforcement Learning. Data Scientists may find the hands-on DeepSeek prompting sessions quite useful. The course's exploration of DeepSeek's architecture and programmatic access may enable data scientists to integrate and experiment with cutting-edge AI models. Data Scientists who wish to leverage the latest advances in AI should consider this course.

See salaries and explore the career path for Data Scientist

AI Product Manager

An AI Product Manager guides the development and launch of AI-driven products. This course provides an understanding of AI and ML principles, which is essential for making informed product decisions. It covers Deep Learning, Generative AI, and advanced AI topics. The course's hands-on DeepSeek prompting sessions and exploration of DeepSeek's architecture can provide valuable insights into the capabilities and limitations of AI models. The comparison of DeepSeek's API costs with other services like OpenAI's ChatGPT can help Product Managers make strategic decisions about resource allocation and pricing. This course will benefit AI Product Managers.

See salaries and explore the career path for AI Product Manager

Cloud Solutions Architect

A Cloud Solutions Architect designs and implements cloud-based solutions. This course helps provide a solid foundation in AI and ML, which is increasingly important for cloud-based applications. The course's coverage of programmatic access to DeepSeek through APIs and platforms like Amazon Bedrock may prove highly relevant. Gaining proficiency in integrating DeepSeek into cloud environments and understanding its cost-effective advantages can aid Cloud Solutions Architects in designing optimized and scalable AI solutions. Cloud Solutions Architects can utilize this course to enhance their skills.

See salaries and explore the career path for Cloud Solutions Architect

Software Architect

A Software Architect designs and oversees the implementation of software systems. This course helps provide insight into AI and ML. The course's detailed exploration of DeepSeek's architecture and programmatic access, including integration with platforms like Amazon Bedrock, may enable Architects to design AI-powered solutions effectively. The practical examples and hands-on sessions may allow architects to incorporate cutting-edge AI technologies into their system designs. A Software Architect might find this course to be quite illuminating.

See salaries and explore the career path for Software Architect

Full-Stack Developer

A Full Stack Developer works on both the front-end and back-end of web applications. This course can provide a foundation in AI and ML, and further explore deep learning and generative AI could broaden a developer's skill set. The hands-on DeepSeek prompting sessions may help developers integrate AI features into their applications more effectively. Learning how to programmatically access DeepSeek through APIs can enable developers to build intelligent web applications. The insights on cost-effective AI solutions may assist developers in making informed technology choices. The Full Stack Developer should consider this course.

See salaries and explore the career path for Full-Stack Developer

AI Ethics Officer

An AI Ethics Officer ensures the responsible and ethical development and deployment of AI systems. This course helps provide insight into the underlying technologies of AI, including Deep Learning and Generative AI. Understanding the internals and architecture of models like DeepSeek may help you assess potential biases and ethical considerations. This course can help inform the development of ethical guidelines and frameworks for AI implementation. For an AI Ethics Officer, this course may be quite beneficial.

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Data Engineer

A Data Engineer designs and builds systems for collecting, storing, and processing data. While not directly focused on data engineering, this course helps provide a foundation in AI and ML. It may give data engineers a better understanding of the data requirements and processing needs of AI applications. The knowledge gained can improve your ability to build efficient and scalable data pipelines for AI initiatives. The data engineer career role may find this course useful.

See salaries and explore the career path for Data Engineer

Technical Writer

A Technical Writer creates documentation for software and hardware products. While not directly focused on technical writing, this course offers foundational knowledge in AI, ML, and generative AI. This course may provide the Technical Writer with a better understanding of the technologies they are documenting. The knowledge gained may help in creating accurate and informative documentation for AI-related products and technologies. The technical writer career role may find this course quite useful.

See salaries and explore the career path for Technical Writer

DeepSeek & Generative AI Masterclass for Software engineers

What's inside

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Syllabus

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Reviews summary

Practical deepseek & generative ai for engineers

Activities

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