
Practical AI Short-Form Ad Production with Midjourney
greenonlinecamp
For learners unsure of what to create, we provide guidance from planning through short-form completion based on hands-on production experience.
Beginner
AI, ChatGPT, Midjourney
We solve the challenge of knowing Python syntax but struggling to build services through hands-on experience at Naver and step-by-step practice.
1 learners are taking this course
Level Basic
Course period 12 months
Implement practical programs using Python variables, data types, conditional statements, and loops.
Write maintainable code by applying functions, modules, exception handling, and the fundamentals of object-oriented programming.
Collect, clean, and analyze data with pandas, and build data pipelines needed for AI services.
We develop AI features by connecting the ChatGPT API and prompts to Python, considering cost, errors, and response quality.
Understand the core principles of classification models and Transformers, and apply suitable AI features to services.
Implement the input and results screens with Streamlit, then deploy it as a genuinely usable AI web service.
Test and improve the completed service, then organize it into a portfolio-quality deliverable.
I know Python syntax, but why do I get stuck before building a service?
Drawing on my hands-on experience at Naver, I guide you through connecting everything from variables and loops to data processing, AI features, and web service deployment.
Build conversational AI features while considering errors and costs, and complete a fully functional deliverable with Streamlit.
Go beyond syntax and build services yourself that become part of your portfolio.
It progresses step by step from Python fundamentals to web service implementation. Starting with variables and loops, you will complete everything from data processing and artificial intelligence features to interface implementation yourself.
This section covers how to apply data and artificial intelligence features to your work. You will clean data with pandas and connect the ChatGPT API to implement features while considering costs, errors, and response quality.
Drawing on practical experience at Naver, you will enhance the quality of your deliverables. Build an executable AI web service with Streamlit, refine it through testing and improvements, and organize it into a portfolio.
Green Online Camp has developed training that connects what learners have learned to real-world work amid the rapidly changing information technology and artificial intelligence landscape.
Even after learning the syntax, it is easy to get stuck when it comes to processing data and implementing AI features as services. That is why, drawing on practical experience at Naver, we designed a learning path that directly connects everything from Python basics to pandas, the ChatGPT API, transformers, and Streamlit deployment.
See for yourself how code turns into a finished product.
Connect Python syntax to real-world tasks. Clean and analyze data. Integrate AI features into service interfaces. Your completed projects will become the starting point of your portfolio. Now, build it yourself.
Learn the core syntax from installing Python through variables, data types, strings, conditional statements, logical operators, and loops. Implement practical programs using data structures such as lists and dictionaries, as well as advanced loops.
Learn how to deepen your understanding of data structures and apply exception handling to write stable code. Use the core concepts of object-oriented programming, along with classes, modules, and packages, to build maintainable programs.
Learn data collection, cleaning, analysis, and preprocessing pipelines using pandas, and strengthen the data processing skills needed to develop AI services through ChatGPT and API integration..
Understand the core principles of classification models, transformers, and attention, and build services by combining Python classes with AI functionality. Use streamlit to create user input and result screens, and develop web services with practical applications.
Learners who want to expand their Python fundamentals into practical AI services
Learners who want to implement AI features as a web service and build a portfolio
Practice environment
Windows and Mac operating systems are supported.
Python and Streamlit must be installed.
We also use Pandas and the ChatGPT API.
At least 8 GB of memory is recommended.
An internet connection and a code editor are also required.
Prerequisites and Notes
It is recommended that you have a basic understanding of Python syntax.
We cover the material step by step, starting with variables and conditional statements.
You will apply functions and loops in practice.
Object-oriented programming and data processing follow as well.
An API key is required to use the API.
Please check the costs based on usage.
Learning materials
You can refer to the lecture slide PDF.
We use Python practice code and data examples.
We provide materials on pandas analysis and preprocessing.
ChatGPT API and Streamlit examples are included.
The course is structured around the process of building AI web services.
Who is this course right for?
Learners who are new to Python or want to apply basic syntax in practice
Aspiring developers who want to create projects featuring data processing and AI capabilities beyond grammar learning
Planners and developers looking to automate tasks or build web services using the ChatGPT API and AI models
Learners who want to quickly build prototypes with Streamlit and experience deploying them.
Learners seeking to develop intermediate-level AI service development skills and build a portfolio based on basic Python experience
All
16 lectures ∙ (6hr 58min)
Course Materials:
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