This is a course for beginners to master the fundamental techniques of the entire Python data analysis process. As an e-commerce planner and developer currently applying data analysis techniques in the field, I have designed this course to help you easily learn and immediately apply the entire Python data analysis workflow.
먼저 경험한 수강생들의 후기
5.0
데싸데분
I'm continuing this course after taking the Web Scraping Basics Bootcamp! I'm currently taking other bootcamps in parallel with the goal of becoming a data scientist, and from a beginner's perspective, Fun Coding's lecture quality seems truly overwhelmingly excellent! Going forward, I plan to actively use Fun Coding's lectures for preview purposes, while focusing on review and project work in other bootcamps! Thank you sincerely for the great lectures and passionate feedback every time! I'll see you again in the next lecture 😊
5.0
gyunhwank
This course was structured around practical exercises covering data preprocessing and EDA using Pandas, and visualization through Plotly, which was a great help in learning the flow and feel of data analysis. By applying the various features of Pandas to actual datasets, I became familiar with the analysis process, and through Plotly, I could create intuitive visualization results, allowing me to develop my data interpretation skills as well. As someone learning data analysis for the first time, the practical-oriented structure was particularly useful, and because the instructor's explanations were kind, it was a course that even non-majors could follow without difficulty.
5.0
박해성
Overall, it was very helpful for me to learn, and I could see the instructor's love for teaching. I hope that in the future, as you mentioned in the middle of the lecture, you will provide easy-to-understand lectures on a wide range of topics.
How to use pandas
Data Analysis Basics
Python Data Preprocessing
Latest Data Visualization
Plotly visualization library
Various data formats and data collection
This course is a lecture for learning Python data analysis techniques. It is designed to help you master everything from data preprocessing and data manipulation using the pandas library to the most useful modern visualization library (plotly). Drawing on 8 years of experience teaching 80,000 students while working in the field, this is a special course created with the learner's perspective in mind more than typical IT lectures, providing detailed additional materials alongside the lessons.
This course is currently being used as an official in-house Python data analysis training program at one of the top-tier tech companies (Naver, Kakao, Line, Coupang, Baemin).
Experience the entire process of data collection, preprocessing, and analysis (SQL/NoSQL + Python). If you want professional analysis skills, master the Python-based techniques in this course. If you aim to become a data analyst or scientist, we provide a roadmap for step-by-step learning from the introductory level. (Refer to the Data Analysis/Science Roadmap at the bottom)
I have created a video that explains data-related careers and the entire analysis/science process in detail. Through this video, you can efficiently learn the data curriculum through self-study according to your goals.
Everyone already possesses the basic knowledge for data analysis. Knowing how to calculate an average is enough. The key is to quickly master the skills to perform the entire data analysis process using Python.
Python data analysis is not a simple skill that can be mastered all at once. To build proficiency, you need to become 'familiar' with it, which is achieved more effectively when you encounter similar concepts from various angles and learn through multiple application examples. To this end, I would like to introduce the following book I authored, which will be helpful to reference alongside this online lecture. By utilizing both resources, you can become familiar with Python data analysis techniques in a shorter period of time.
Python data analysis can feel very unfamiliar at first. By using online lectures to learn how to use relevant tools and watching real-time code execution, you can effectively learn practical workflows and difficult concepts.
After building a solid foundation through online lectures, you can become more familiar with concepts and syntax by encountering different explanations and additional examples of similar grammar through books. This will help you develop the ability to apply Python data analysis techniques to various types of data.
The data field is a combination of various theories and technologies. Therefore, it is important to learn them systematically. Rather than lectures that assume you already know all the relevant theories and jump straight into analyzing data and applying flashy machine learning or AI techniques, lectures that allow you to learn the necessary theories and skills from a beginner's perspective one by one, practicing and building them as your own, are more helpful.
Kaggle competitions primarily involve predicting data using machine learning and AI. To master these technologies, you must first become familiar with data analysis skills such as pandas. This course covers pandas and visualization techniques, and is structured to help you learn machine learning and deep learning (AI) technologies step-by-step through a systematic roadmap. (Refer to the roadmap below)
In the industry, data is primarily analyzed using SQL and pandas. Professional data analysis requires skills in data preprocessing, analysis, and visualization. To achieve this, you can master pandas and plotly. This course covers all the core technologies needed for professional data analysis using Python in the field.
Pandas has a high barrier to entry due to its unintuitive syntax and vast range of features, requiring significant practice. This course has been structured with these challenges in mind:
Through this, the course is designed to help you become familiar with pandas and plotly in a short period and master the entire process of Python data analysis.
However, it is difficult to take a lecture that requires you to first understand various fields you aren't even interested in. Try analyzing the e-commerce data covered in this course. Even without using the term "untact era," all businesses have been shifting online over the past few years. To understand online business, try understanding e-commerce data, which is the most core element. Both understanding the most helpful domain and the related technologies will be of great help.
We provide summarized explanations that go beyond the limits of a book, along with actual code in a format that can be executed immediately. By watching the lectures and running the materials together, reviewing becomes easy, and you can refer back to them whenever needed in the future. (I am very attached to the materials. I create materials that are better than books, so that the materials alone make the tuition fee well worth it.)
matplotlib is a traditional but limited data visualization technology that primarily focuses on creating static graphs. In contrast, the modern technology plotly focuses on creating interactive graphs that allow for user interaction. Furthermore, it offers advantages such as superior visual quality, suitability for web environments, and support for a wider variety of graphs. As a result, plotly has recently become the mainstream choice in the industry. Therefore, this course explains plotly technology, which is becoming the dominant visualization skill.
To make Python data analysis skills your own, various practical exercises are necessary. This course conducts data analysis from start to finish using various real-world examples (COVID-19 data preprocessing, e-commerce data analysis). Through this, you can increase your proficiency in related technologies and organize the knowledge you might have missed.
시간을 낭비하지 마세요!
This is a course created through constant reflection and improvement
so that you can truly feel, 'Ah! This is really different!'
I kindly ask that only those who are reasonable, considerate,
and looking to build a good connection
take this course!
A data preprocessing example created by processing actual raw data in a data lecture
COVID-19 data is the most helpful example for practicing actual pandas basic functions and preprocessing. Therefore, the course is structured to help you firmly master the relevant skills by creating graphs for the entire period when COVID-19 was most active, as follows:
Daily trends of confirmed COVID-19 cases by country (including the entire tracking period of confirmed cases during the pandemic)
Career Roadmap for Developers, Data Analysts, and Data Scientists!
From web/app development to data analysis and AI, we provide an A to Z roadmap to build a solid foundation in a short time. IT technologies are closely interconnected, and integrating them enables web/app services and data science. By gradually increasing difficulty and mastering core technologies, you can learn efficiently, understand systems and data comprehensively, and grow into a competitive developer or data professional. To achieve this, we've prepared a roadmap that systematically organizes the core technologies of each field.
I have created a video that explains this roadmap, data-related careers, and the entire data analysis/science process in detail. By referring to this video, you can easily master the data process in a short time on your own without any trial and error!
Wait! ✋
Click the roadmap below to see more details. If you purchase the roadmap as a bundle, it is offered at a discounted price! (The discount rate is scheduled to be reduced soon.)
I have created a video explaining in detail this roadmap and how to learn and implement web/app development on your own in the fastest way possible. By referring to this video, you will be able to implement web/apps without trial and error in a short period of time.
Wait! ✋
Click the roadmap below to see more details. If you purchase the roadmap as a bundle, it is offered at a discounted price! (The discount rate is scheduled to be reduced soon.)
This roadmap is a course that systematically organizes essential Computer Science (CS) knowledge, which serves as the foundational IT theory for the development and data fields. Among these, we are offering lectures that allow you to systematically master the most critical core subjects, such as computer architecture, operating systems, and networks.
학습 대상은 누구일까요?
Those who want to master Python data analysis techniques
Those who want to master pandas and visualization techniques
Those who want to grow as data analysts in the long term
Those who want to master data analysis skills in the long term
Those who want to build a solid foundation in basic data analysis skills.
33,600
수강생
2,473
수강평
1,949
답변
4.9
강의 평점
13
강의_other
Janjemi Coding, Dave Lee
Key Experience: Senior Engineering Manager/Principal Product Manager at Coupang, Engineering Manager at Samsung Electronics (approx. 15 years of experience)
Education: BA in Japanese Language and Literature from Korea University / MS in Computer Science from Yonsei University (A total mix)
Key Development History: Samsung Pay, E-commerce search services, RTOS compiler, Linux Kernel Patch for NAS
Books: Linux Kernel Programming, Understanding and Developing Linux Operating Systems, IT Core Technologies for Everyone to Read and Understand, Python Programming Primer for Absolute Beginners
Official Website: Fun-Coding (http://www.fun-coding.org) [Click]
This site shares free resources related to full-stack development, data science, and AI.
Others: Fun-Coding YouTube Channel [Click]
I'm starting to share tips and short free lectures little by little to help with IT learning!
For eight years, I have been consistently creating solid full-stack, data science, and AI courses while balancing my work in the industry with teaching IT.
I am gradually starting to share my lectures. Balancing my current industry experience with teaching, I have been consistently creating solid full-stack, data science, and AI courses for 8 years.
전체
58개 ∙ (강의상세_런타임_시간 강의상세_런타임_분)
전체
351개
4.9
351개의 수강평
수강평 2
∙
평균 평점 5.0
5
The materials in the provided Jupyter notebook are neat and easy to read, and the practice of graphing the trend of confirmed COVID-19 cases by country is good. If you ask a question you don't know, they will answer quickly and sincerely, and there are no points to deduct. 5 out of 5. The explanations are also good and not difficult.
수강평 2
∙
평균 평점 5.0
5
Thanks to the A-Z approach with detailed explanations for each topic, I feel like I'm building knowledge from the ground up. No matter what subject you're studying, finding the right course and instructor that fits you is the most important thing, and I think I've found mine.
Thank you!!
수강평 81
∙
평균 평점 5.0
5
Thank you very much. It was a great help. I am very satisfied with the lecture content and lecture materials. I am also looking forward to the machine learning lecture. ^_^
I am so glad that it was helpful. I will also use the course reviews you wrote to encourage me, always think about them, and try to make better lectures. I really work hard on the lecture materials. I also enjoy making materials. I am so glad and happy that you are satisfied. Please do not open it to the outside, and use it only for personal use. Thank you.
수강평 5
∙
평균 평점 5.0
5
As a coding beginner, I started with nothing, starting with the Python bootcamp lecture, then the crawling lecture, and now I have finished the Python data analysis lecture. Although these lectures may seem like separate lectures on the outside, they have a single flow and purpose as they always emphasize during the lectures, and most importantly, they explain in detail and in an easy-to-understand manner from the perspective of a non-major, so I was able to take the classes comfortably. I am currently working in the real estate business, and after taking these lectures, I gained the ability to process and utilize data provided by sites such as Naver Real Estate and public data portals as I want. It may seem lacking to experts, but I think that having this ability as a real estate business owner who is not an IT expert is a really great weapon. Also, there is a huge difference between passively looking at processed data provided by others and looking at data that you have processed yourself. So, if you are just starting out like me, don't worry too much and follow Janjaemi Coding's lectures one by one, you will find yourself growing before you know it. And if there's one thing I wish for, it would be great if there was a lecture that completed a project from start to finish (even if the lecture length is relatively short) based on the lectures I've taken so far (Python Bootcamp, Database, Crawling, Data Analysis, etc.). I'm now going to listen to SQL and NOSQL that I missed in the middle!!!! (My goal is to take all of Janjaemi Coding's lectures this yearㅎㅎ) Thank you for the great lecture and I will continue to trust and follow you in the future.
Ah... such a good course review... you must have spent some time on it... thank you. I'm a little touched again. In my opinion, developers only know IT, but people in other fields have expertise in their own fields. Since there are not many people in each field who know IT well, I think that if you have your own expertise and can utilize IT, you can have a huge impact. However, it is very difficult to create such a lecture or absorb such a lecture. Nevertheless, through this lecture, I really like that you actually analyzed real estate data with Python. I think it's because the students are that smart. Thank you.
수강평 3
∙
평균 평점 5.0
5
I am a student who aims for graduate school and research in deep learning, machine learning, and mechatronics. So I took Python lectures from other instructors to build up my basics, and I took this lecture to learn the data processing and analysis process. At first, unlike other instructors, he didn't write the source code while filming videos, but prepared class materials and lectured on the content in detail. Most of the lectures I took were from the former, so it took me a while to get used to the latter. However, the materials related to the class content were really solid. I really liked this part. Also, as the class progressed, what impressed me the most was that even though the class was just continuing, it was repetitive learning. For me, the most difficult thing about listening to lectures is repetitive learning. In the case of academies, they make students repetitive learning through assignments, but on average, many students, including me, find repetitive learning difficult or boring through lectures. However, this lecture was a very helpful lecture for me because it allowed me to learn new content while repetitive learning. Of course, I plan to take other classes again and challenge myself with repeated learning, lol... When I take this class, I first watch the video all at once. If there is a part that I don't understand, I watch it over and over again. Then, I put down the video, put the materials that the teacher gave me on one monitor window, and at first, I wrote down the source code as I remembered it, and when I couldn't remember it/when I thought I had finished writing the source code, I checked the materials. In addition, if you post a question on the Q&A board or the video, you will receive a reply in a day or less at the earliest. This is where you can feel the teacher's enthusiasm. Also, one of the things I felt when I took the Python class was that when you ask a question, they give you a link to the relevant content. And I saw some people who lectured by saying that it would be helpful if you referred to it. Personally, I didn't like it, but the instructor of that class put a lot of effort into leaving comments. And, I plan to take a class on MongoDB for the next class! The class was really good ^_^!
Thank you so much for leaving such a great review. It must have taken you a long time to write such a review, but I was actually a little touched that you wrote it in such detail. Reviews like this are a great force that can create good lectures. I tried both the method you mentioned, writing code while doing it, and the method of explaining it with materials and a kind of scenario, but when I did the former, the content I wanted to convey was not conveyed in a substantial way, and since I was worried about both the code and the content I wanted to convey, the learning effect actually decreased. So I decided to use the latter. Actually, answering questions every day is not easy for me either... I'm worried that I'll have to make an announcement when I go on vacation, haha. After all, since I've never met you before, if my answer is not conveyed properly, it's easy for there to be misunderstandings, so I'm paying more attention. When I meet many people online without meeting them in person, there are many cases... Luckily, many people gave me positive reviews, which is a great help. Thank you so much.
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