Mastering DeepSeek: Unlock the Power of the Next-Gen Free AI

Name: Mastering DeepSeek: Unlock the Power of the Next-Gen Free AI
Rating: 4.7 (12 reviews)

Learn DeepSeek from Beginner to Advanced: Explore This Cutting-Edge Generative AI with Real-World Use Cases

Created byJones Granatyr, Gabriel Alves, AI Expert Academy

Last updated 6/2025

English

What you'll learn

Understand the impact of DeepSeek in the generative AI landscape, including its advantages, limitations, and usage best practices
Explore the DeepSeek interface with hands-on tests, file attachment reading, image processing, and web search
Master prompt engineering techniques like role prompting and in-context learning, applied to real-world tasks
Use DeepSeek for content and code generation, translation, proofreading, tone adjustment, and logical problem-solving
Run DeepSeek locally with full privacy using tools like LM Studio, Ollama, and Google Colab
Use DeepSeek via API and in environments like VS Code, regardless of your hardware
Learn how to download models directly from repositories like Hugging Face and set them up properly
Integrate DeepSeek with spreadsheets, emails, and forms to build useful automations without writing any code
Develop real projects such as automatically categorizing form data and logging results into spreadsheets
Build an application using RAG with DeepSeek and Streamlit to create smart document interactions

Course content

5 sections • 31 lectures • 3h 4m total length

Course content7:20
Course materials0:03
DeepSeek - intuition 18:54
DeepSeek - intuition 212:03
DeepSeek - intuition 32:35
DeepSeek Test

Testing the interface5:01
Reasoning model6:53
Prompt engineering6:20
Content creation4:36
Learn to perform content creation with Deep Seek by crafting professional emails and improved texts, using prompts with context to guide generation, schedule meetings, and summarize notes.
Loading files4:33
Internet search3:26
Role prompting6:59
One/few-shot prompting5:29
Explore one-shot and few-shot prompting as the second prompt engineering technique, using examples to guide the model, with zero-shot, one-shot, and few-shot variants to improve accuracy.
Chain of thought prompting3:52
Code generation4:11
Master code generation with DeepSeek by leveraging chain-of-thought prompts to produce browser-run programs that convert kilometres to miles and miles to kilometres, with testing in JavaScript and HTML.
Refining, auto reflexion and templates3:31
Discover prompt engineering techniques—prompt refinements, self reflection, and prompt templates—to improve prompts, ensure understanding, and leverage ready-made prompts from communities and repositories.
Practical Use Test

Implementation using HuggingFace21:53
Learn to implement deep seek with Hugging Face in Google Colab, using Transformers and bits and bytes quantization to load, tokenize, prompt, and generate outputs on a causal LM.
Implementation using API12:45
Implementation using Ollama4:23
Implementation in local machine5:45
Install python and Visual Studio Code, set up the project, configure a .env file, and run sic codes dot py to call the grok API on your local machine.
Local use with LM Studio5:15
Local use with Ollama2:53
Learn to run the basic Ohyama model locally on your computer, install via website or Docker, and interact with the model through terminal commands.
Coding and Local Use Test

Content creation3:52
Organization and productivity3:40
Curriculums4:16
Costumer service3:14
Learn to implement efficient customer service prompts and chat rules that generate ready-to-send, natural responses. Set initial prompts and questions to streamline support and convert inquiries into formal email replies.
Code generation4:28
Automation of forms18:40
Master forms automation by connecting Google Forms to Make through Open Router and Dipstick, classify responses, and log results in Google Sheets for organized data and category-based routing.
Chat with documents using RAG5:16
Learn to chat with documents using a retrieval technique in a Streamlit Python app, loading PDFs with pi pdf in Google Colab via a local tunnel.
Case Studies Test

Requirements

Basic Python programming

Description

Learn everything from the basics to advanced techniques to master DeepSeek, one of today’s most powerful open-source Generative AIs — capable of outperforming even the most advanced ChatGPT models. In this course, you'll explore how to use this revolutionary technology in practice, both with and without programming, always focusing on real examples and useful applications for personal and professional use.

You'll gain a clear understanding of DeepSeek’s impact in the AI landscape, along with its advantages, limitations, and best practices. We start with the interface, including hands-on tests, file reading, image processing, and web search. You'll dive into prompt engineering with techniques like role prompting and in-context learning, and see how they can be effectively applied to tasks such as content and code generation, translation, proofreading, tone adjustment, and logical problem-solving.

Learn through real examples: content creation, math exercises, code generation, and application development. Discover how to download and run the model locally on your own computer — fully private and without requiring an internet connection to run the model. You'll learn how to use DeepSeek through Graphical User Interfaces (using LM Studio), via API, on Google Colab, with Ollama, and with VS Code — regardless of your hardware. You’ll also learn how to choose and download models directly from repositories like Hugging Face.

Additionally, you'll learn how to integrate DeepSeek with services such as forms, spreadsheets, and email, enabling practical automations without needing to write any code. One of the projects developed will be a fully functional solution that reads contact form data, automatically categorizes the information, and records the results in a Google Sheet.

By the end of the course, you'll know how to develop a real-world project using RAG (Retrieval-Augmented Generation), where DeepSeek interacts with documents through a modern Streamlit interface, ideal for those looking to build full-featured AI-powered applications.

Whether you're a coder or not, this course is your gateway to unlocking the full potential of DeepSeek and turning ideas into powerful AI-driven solutions.

Who this course is for:

Anyone interested in Artificial Intelligence who wants to learn how to use generative AIs — with or without coding
Developers looking to explore DeepSeek’s potential and run it locally with full control
Professionals who want to use DeepSeek to generate ideas, improve writing, and translate more efficiently
Developers aiming to integrate DeepSeek into their own applications, without relying on paid APIs
Students and self-learners who want to understand and experiment with generative AI through real-world use cases
Tech professionals or enthusiasts looking to connect DeepSeek with tools like spreadsheets, forms, and web apps
Individuals who want to master open-source models like DeepSeek without being limited to closed solutions like ChatGPT

Mastering DeepSeek: Unlock the Power of the Next-Gen Free AI

What you'll learn

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Course content

Introduction5 lectures • 31min

User interface11 lectures • 55min

Source code and local use6 lectures • 53min

Case studies7 lectures • 43min

Final remarks2 lectures • 3min

Requirements

Description

Who this course is for: