Automotive SW R&D for Job Seekers

Learn the basic concepts of Autosar for automotive SW development.

Learn and understand the many services of ISO 14229-based UDS that are widely used in practice.

We explain the core basic knowledge required for AUTOSAR-based automotive software development, covering everything from beginner concepts to very detailed content, in a way that even a novice can understand.

You'll gain a very clear understanding of what diagnostic communication is in automotive SW roles, and what a diagnostic communication practitioner does and how! This lecture provides content specific enough for practitioners to immediately start work with actual spec documents.

This is a process for completing IoT products without complex coding, using the Vibe Coding methodology powered by AI agents. You can experience the entire product development cycle in a condensed format—from embedded hardware control and AI vision recognition to PCB design, 3D printing, and web/app service development—allowing you to launch functional, commercial-grade IoT devices.

We understand the essence of the job market through concepts from economics and statistics, and use this foundation to redesign job-search and career-change strategies as a data-driven probability problem rather than relying on intuition or competing over credentials. Instead of accumulating more qualifications, we shift the game to a rational “market” by directly collecting and analyzing job-posting and company data with AI to identify markets and openings where the likelihood of success is high. By using AI as a tool built on core concepts from economics and statistics, we systematize application, interview, and job-search strategies, presenting a way to develop a data-driven approach to employment that even non-majors can understand. We also directly build a recruitment AI assistant that works 24 hours a day exclusively for me—using AI-based vibe coding accessible even to non-majors—which can be used immediately as a portfolio project in actual job preparation.

Are you using code written by AI without even knowing what it does? It’s not enough for it to simply work—you need to make it perform well, yet when asked, “Why did you implement it this way?” you find yourself at a loss for words. The source of that frustration is a lack of fundamental CS knowledge and an understanding of how GPUs work. Through this course, you will learn the principles applied to CPUs and GPUs, along with the relevant CS knowledge, enabling you to control AI and give it instructions effectively. You will also be able to avoid being replaced by AI at your current company or when seeking employment or changing jobs, and earn a higher salary.

Gain insights from DataOven CEO Ha Yongho, a first-generation data analyst who has demonstrated numerous insights and successes. This is a meetup video for data professionals, held on July 18, 2024.

As you study CPUs and RISC-V, you may understand what the instructions do but still find yourself asking, “How are these instructions actually executed in hardware?” and “How can I verify that a CPU I designed myself really works correctly?” Many existing resources stop at ISA explanations or simple CPU examples, and many others rely on completed IP, making it difficult to experience the entire process of designing and verifying a CPU yourself and running programs on an actual FPGA. I have spent many years working in R&D and business in the system semiconductor field, and I have observed this learning gap firsthand while teaching semiconductor design and FPGA at a university. For this reason, rather than providing a completed CPU and simply checking that it operates, this course is structured around designing the CPU directly in a White Box approach, starting with the question, “What hardware is required to execute RV32I instructions?” In Volume 3, we expand Volume 2’s TinyRV32I into a Full-Version 32-bit CPU that uses 40 RV32I instructions. We extend the datapath, Decoder, Branch·Jump, and Byte/Halfword Memory Access, and implement Forwarding and Load-Use Interlock so that the 5-stage Pipeline can handle data dependencies on its own. We then integrate CSR, Exception, Interrupt, Trap, and MRET to complete a CPU capable of handling not only normal program execution but also exceptions and external events. The design does not end with RTL Simulation. You will run actual programs on the CPU, compare the results with the Spike Reference Model, and learn the purpose of the RISC-V Architecture Compatibility Test as well as how to perform and evaluate it through real verification cases. Finally, you will implement the verified CPU on an Arty S7-25 FPGA, receive input from Switches and Buttons, run programs, and confirm the results by displaying them on LEDs. The problem this course aims to solve is not simply learning more RISC-V instructions. Its goal is to connect instructions → CPU architecture → Verilog RTL → Pipeline control → program execution → standards-based verification → actual FPGA operation into a single flow, enabling students to fundamentally understand the internal structure of a CPU and develop the engineering skills to design and verify one themselves.

Many people have learned FPGA and Verilog but get stuck at the question, "So, how do I actually build an AI accelerator?" This course resolves that curiosity. Using just a single entry-level FPGA and free tools, you will start from a hand-designed 3×3 kernel, train a CNN yourself, quantize the trained weights to INT8 to load onto the hardware, and verify that the results are Bit-True—not deviating by even a single bit from the Python model. As a professor with 30 years of experience in the semiconductor industry, I teach only verified content as 'working circuits' on actual FPGAs. By gaining the experience of designing and proving it yourself rather than just learning theory, you will acquire practical skills that are recognized in the fabless design and AI semiconductor fields.

Starting from the operating principles of RISC-V instructions, this is a hands-on CPU design course in which you directly design a 32-bit CPU with a five-stage pipeline, completing the process from Verilog RTL implementation and simulation verification to running it on a physical FPGA. Among the 40 RV32I instructions, 14 instructions essential for learning the core structure of a CPU are selected to progressively build TinyRV32I. You will directly design and verify the key structures that make up a real CPU, including the datapath, pipeline registers, ALU and control circuits, branches, hazards, stalls and flushes, and memory-mapped I/O. The Verilog RTL, testbenches, assembly programs, memory images, and FPGA constraint files used in the course are provided. Ultimately, you will run actual programs on an Arty S7-25 FPGA using the CPU you designed. This course does not end here. After completing the core CPU structure through TinyRV32I, the series continues as a step-by-step CPU design program in which you expand it into a Full RV32I CPU supporting all 40 RV32I instructions in the follow-up course.

This course is part of the 'Wrtn AI Literacy Voucher Program', a collaboration between Inflearn and Wrtn, and is available completely free for job seekers who are vulnerable to AI. Career expert Career D will teach you step-by-step how to apply AI to job searching and career transitions. From basics to hands-on practice, it's designed so that even AI beginners can follow along easily without any burden!

After using it for 14 days starting immediately upon release, here are the reasons why I recommend Claude Code (AI Coding) to everyone—from job seekers to industry professionals—as something they can apply right away.

No more outdated PPTs even after working all night! A veteran instructor with 25 years of experience has packed in only the essential core skills needed for practical work, from PowerPoint basics to the latest AI utilization methods. Even without design sense, we'll teach you 'everything about presentations' that cuts your work time in half and doubles your quality.

Recommended for these students! Frozen~! Coco! I watched it too~ But how was it made? I want to major in animation too, but is this really what I want to do? Can I learn everything once I enter a university program? What should I prepare for employment? Should I just watch a lot of animations? That animation looks like it has a different style - I want to know how it's produced AI has advanced too, can't I make it on my own? I want to get a job at an animation company - any tips? In this class, you'll learn: ✔ Animation genres, fields, concepts, and all the production processes needed for creation! ✔ What are the actual working departments in animation companies? Which departments play what roles as the gears turn in the production process? ✔ Concepts, production, management, and even hands-on practice! Once you complete all of this, you'll become an animation master who understands the concepts even better than animation majors!

"Simply knowing technology well does not make you a good sales engineer." Understanding customers’ problems, connecting technology to business value, and exerting influence between sales and development are the core responsibilities of a sales engineer. In this course, drawing on more than 20 years of B2B software presales experience, I will systematically share practical know-how on customer meetings, requirements analysis, demos, PoCs, proposal strategies, and internal collaboration. Learn the work frameworks and mindset of a sales engineer that you can apply immediately in practice.

Learn the core concepts and operating principles of Physical AI, which moves beyond the screen to be implemented in robots, autonomous vehicles, and drones. Understand the sensing-perception-action mechanism, digital twin-based learning, and the importance of embodied data, while exploring the global technological competition and Korea's strategic direction through real-world cases in industries such as manufacturing, mobility, and agriculture.

Complete Understanding of Robotics High- and Low-Level Controllers, Sensors, and Ultra-High-Speed Communication Concepts Through the Unitree Go2 Example

"AI will not replace people. People who master AI will replace those who rely on it." In the era of AI, where creating results has become easier than ever, human thinking and problem-solving skills are becoming even more critical. Jae-sung Kim, a former McKinsey consultant, will guide you step-by-step through advanced problem-solving skills using AI, powerful research strategies, and persuasion techniques to turn your results into reality.

Learn how to turn a vague idea into a "completable work." The reason you fail to finish writing on your own is not a lack of talent, but a lack of planning, structure, genre, and scene-level design. Based on my Master of Fine Arts (MFA) in Screenwriting, over 10 years of writing experience, and the achievement of winning two awards with a single work, I will organize professional-standard writing techniques step-by-step online. In this main lecture, "Chapter 1: Film Planning," we will cover everything from planning methodologies to writing loglines and statements of intent, while also learning prompt engineering to utilize AI as a planning and assistant writer. Ultimately, you will work with the instructor to complete a one-sentence logline for the project you wish to write. The course proceeds with the perspective that the writer's judgment and design are what matter most, while AI is simply a tool that makes that process more efficient. The full curriculum for [Film and Drama Storytelling in the AI Era: Story Design for Creating Works and Careers] follows a 5-chapter roadmap: Film Planning → Structure → Plot & Character → Genre → Scene & Adaptation. By following each step, you can eventually expand your work into a full-length feature film screenplay (or a series proposal + scripts for episodes 1-2, depending on your goal). (Note: This course is sold individually by chapter.)