Codex with Silicon Valley Engineers
altoformula
From a developer who only used ChatGPT to a developer who handles AI agents. Learn practical ways to maximize coding productivity using Codex's Rules, Hooks, Skills, and MCP.
Beginner
AI, Python, codex
Now, your AI is no longer in the cloud. It runs directly inside your laptop. Using LM Studio and Ollama, we will show you how to build a Private AI environment that runs entirely locallyโ from data processing and document analysis to code generation. Without security concerns, without costs, and even fasterโ Move beyond simply "using" AI and start "truly mastering" it.
Reviews from Early Learners
5.0
Reo
I took this class to build things like Hermes agents or an LLM Wiki. You explained Ollama and LM Studio, but it would be great if you could also add something about Docker Model Runner. It was also fun to see how the responses changed while adjusting the Temperature during translation. Thanks to that, Iโve become interested in LLM parameters as well. Thank you.
5.0
์๋ฒ์งํด์ด
I've always wanted to run LLMs locally, but I couldn't because the setup was so difficult...? I was able to run it right away after watching this lecture lol. Thank you so much!
5.0
๋ฒ๋ ค๋ผ๋ฐฐ๋ฅผ (๋ฐฐ๋ฅผ๋ฒ๋ ค๋ผ)
I had been using LM Studio and Ollama just by turning them on without much thought, so it was great to have a lecture where I could overall learn about all their features and purposes.
The ability to build a Private AI environment to run AI directly on my own computer
AI workflows for securely processing company and personal data
Transitioning from the "level of using AI" to the "level of operating AI"
A Silicon Valley Staff Software Engineer will teach you everything about running AI directly on your laptop and building a Private AI using LM Studio and Ollama.
Now, utilize AI however you want while keeping your data safe, without worrying about API costs or security.
Have you been hesitant to use ChatGPT due to company security concerns?
Have you been spending time every single time on repetitive data processing, document analysis, and code generation tasks?
Have you felt that your use of AI is limited due to API usage limits and cost burdens?
Don't worry. Through this course, you can take a step forward from 'using' AI to 'directly operating' it.
Now, your laptop will transform into a powerful AI development environment.
Become a 'developer who operates' AI
without worrying about
security and costs.
You can freely utilize AI without worrying about personal information leaks.
Have you ever hesitated to use ChatGPT because of your company's security policies? Through this course, you will learn how to run AI models directly on your laptop using LM Studio and Ollama, allowing you to safely analyze and utilize sensitive company data or personal information without worrying about external transmission. You will no longer feel restricted in your use of AI.
Automate repetitive development tasks and maximize work efficiency.
If you are a developer or data professional who has struggled with a lack of time due to repetitive data processing, document summarization, and code generation tasks, you can now automate these workflows with your own self-built Private AI environment. Transform your laptop into a powerful AI development tool without the burden of API costs or usage limits.
Become an expert who freely operates AI models without the burden of API costs.
Beyond simple installation of LM Studio and Ollama, you will gain the ability to freely manage detailed model settings (Top K, Top P, Temperature, etc.), utilize GGUF and MLX Runtimes, configure system prompts and presets, and integrate REST APIs. Through this, you will advance from the level of simply 'using' AI to 'directly operating' it, acquiring the capability to utilize AI in a cost-effective manner.
Now, your AI runs directly on your laptop, not in the cloud. You will learn how to build a Private AI that performs data processing, document analysis, and code generation directly in a local environment using LM Studio and Ollama. You can elevate your skills from simply 'using' AI to 'actively leveraging' it, all without worrying about security or costs.
In this course, you will install LM Studio and Ollama yourself and build a local AI environment by adjusting various model parameters and settings. You will practice every step necessary for actual developmentโincluding system prompt configuration, Top K/P sampling, and generating structured outputsโto complete an AI workflow that securely processes company or personal data.
We provide the LM Studio and Ollama installation files used in the lecture, along with essential configuration guides and example code for adjusting various model parameters. Additionally, you can obtain all the materials necessary for Private AI development, including Hugging Face open LLM model information, license comparisons, and instructions on how to utilize GGUF and MLX runtimes.
Section 1
Understand the concept of Open LLMs, the types of open-source models, and the importance of model parameters and weights. Additionally, explore model execution in local environments, customization, and the advantages in terms of privacy and control.
Section 2
Install LM Studio and become familiar with the user interface, settings, system prompts, and sampling techniques. Learn how to effectively operate local AI models by studying GGUF, MLX runtime, hardware configuration, context length management, and REST API utilization.
Section 3
Learn how to install and use Ollama, and discover how to find useful open LLMs. This section covers multimodality support, adjusting system messages and model parameters, session management, creating models via Modelfile, and utilizing the Ollama server (API) with code examples.
Those who feel restricted in work automation because they are uneasy about sending sensitive company data to external APIs
Those who find it difficult to focus on core development tasks because they lose time to repetitive daily code generation or document analysis tasks
Those who have installed LM Studio or Ollama but feel overwhelmed by complex settings and parameters,
making it difficult to actually build and utilize a Private AI.
Practice Environment
Operating System: Windows, macOS, and Linux are all supported.
Essential Tools: LM Studio and Ollama will be installed and used.
Recommended Specifications: A PC with a GPU (8GB VRAM or more recommended) and 16GB RAM or more will help with smooth practice.
Prerequisites and Important Notes
It is even better if you have experience in developer or data-related roles.
It is suitable for those who want to run AI models directly on their local machines.
This is a great choice if you are hesitant to use cloud AI due to personal privacy or corporate security concerns.
Learning Materials
Lecture slide PDF materials are provided.
It includes all the code examples needed for the practice.
It is also good to refer to the official documentation for LM Studio and Ollama.
Who is this course right for?
Those who feel frustrated because they cannot use ChatGPT freely due to company security policies
Developers and data professionals who lack time because they are manually performing repetitive tasks every time.
Those who feel restricted in using AI due to API costs and usage limits
Those who have only installed LM Studio and Ollama but haven't been able to utilize them properly.
Need to know before starting?
Basic computer literacy - experience with running a terminal (commands) and installing programs required
Basic understanding of development or data tasks
Experience using AI tools (ChatGPT, etc.) at least once (Recommended)
Inflearn Verified
25,576
Learners
1,447
Reviews
368
Answers
4.8
Rating
32
Courses
Are you going to finish in Korea? Penetrate the global market with English! ๐๐
Hello. I majored in Computer Science (EECS) at UC Berkeley ๐ป, have worked as a software engineer in Silicon Valley for over 15 years, and am currently a Staff Software Engineer working with Big Data and DevOps at a Big Tech headquarters in Silicon Valley.
๐งญ I would now like to share the technologies and know-how I learned firsthand at the forefront of innovation in Silicon Valley with all of you through online lectures.
๐ Join me, having learned and grown at the forefront of technological innovation, and develop the skills to compete on the global stage!
๐ซก I may not be the smartest, but I want to emphasize that you can achieve anything if you stay consistent and never give up. I will always be by your side, supporting you with great resources.
All
28 lectures โ (3hr 9min)
Course Materials:
All
30 reviews
4.8
30 reviews
Reviews 1
โ
Average Rating 5.0
Edited
5
I took this course because I needed to implement a Local LLM, and it helped me establish a clear direction. Although I cannot apply it directly to the specific problem I was trying to solve, it was great to learn how to use LMStudio and Ollama, and to gain other useful information.
Hello hbsong25, Thank you for taking the time to leave such a great review!!
Reviews 18
โ
Average Rating 5.0
5
I took this class to build things like Hermes agents or an LLM Wiki. You explained Ollama and LM Studio, but it would be great if you could also add something about Docker Model Runner. It was also fun to see how the responses changed while adjusting the Temperature during translation. Thanks to that, Iโve become interested in LLM parameters as well. Thank you.
Hello Reo, ๐ Thank you so much for the great review! I see you've registered for this course following the Claude course. I'm glad to hear that the course direction aligns well with your goals of building a Hermes Agent or an LLM Wiki. I'm especially happy that the sections on Ollama and LM Studio were helpful to you. The Docker Model Runner you mentioned is also an excellent point. Since it's an increasingly important area in practical applications, I will consider covering it in a future course update or through additional materials. The fact that you personally experienced how results change by adjusting the Temperature shows that you've really grasped a core concept. Experiencing the principles of how LLMs operate through these kinds of experiments is the fastest way to understand them ๐ Thanks to your great feedback, I believe I can further improve the course. I have updated the content regarding the LLM Wiki in the Claude course, so it would be good to check that out. I will continue to provide updates moving forward. Thank you! ๐
Reviews 4
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Average Rating 5.0
5
I had been using LM Studio and Ollama just by turning them on without much thought, so it was great to have a lecture where I could overall learn about all their features and purposes.
Hello Abandon Ship (Abandon the Ship), Thank you for leaving such a great review! ๐ More people than expected only use the basic features after installing LM Studio or Ollama. In reality, there are many features that significantly increase utility once you know them, such as model management, API servers, context settings, GPU utilization, and comparing various models. Now that you have the foundational knowledge, I believe you'll have even more fun utilizing local LLMs by linking them with AI Agents, MCP, and development tools. Thank you for your valuable feedback!
Reviews 14
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Average Rating 5.0
Reviews 3
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Average Rating 4.3
5
This is a lecture you can use in practice. It is very, very useful.
Hello carpelbr, Thank you so much for the great review! My primary goal was to create a "course you can actually use," so I'm truly glad you felt that way. I will continue to update the content with practical material that can be applied directly to real-world work. Thank you!
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