
Time Series Analysis and Forecasting
루비네코딩
Time Series: Become a Data Analysis Expert! Let's be analysts strong in theory & practice!
Intermediate
Probability and Statistics, Python, Big Data
Finally, the Probability and Statistics course for everyone is here! Learn the principles of probability and statistics step by step through theory and coding practice. Reference book "Probability and Statistics for Everyone" https://wikidocs.net/book/18165
227 learners
Level Basic
Course period Unlimited

Reviews from Early Learners
5.0
박명규
It was nice to be able to see things more broadly than in any other class. I think I can study the details as I go. Thank you to the instructor.
5.0
jsmak
While studying data analysis, there weren't many statistics lectures, but this was a useful lecture. Statistics is heavily weighted in the Big Quarter or ADP exams, so I hope that you are preparing the next lecture, which will be a lecture that can be used a lot in the exam.
5.0
wienprincess
It seems like you are explaining only the essential parts that are necessary for studying math after a long time. The curriculum is very comprehensive. It seems like you have extracted only the essential parts for each topic with appropriate depth. In particular, Markov chains and hidden Markov processes required for NLP were very useful. I liked that it was a lecture that incorporated the instructor's experience rather than a college lecture that just skimmed through the textbook.
Probability theory
Statistics/Predictive Analysis
Statistical Modeling
Python/R usage analysis
어렵기만 했던 확률과 통계는 이제 그만!
데이터 사이언스 커리어를 위해 차근차근 배워봐요 ✏️
확률과 통계를 배우고 싶은데
수학 자체가 너무 어렵게 느껴져요.
데이터 사이언스 기초를 쌓고,
데이터 분석의 원리도 알고 싶어요.
비전공자라서 내가 과연 수학을
공부할 수 있을까 걱정돼요.
이론을 줄줄 설명하기만 하는 강의보다
실제 활용법도 알려주는 강의를 듣고 싶어요.
용어의 100% 한글화이론과 실습을 번갈아 가면서 내공 쌓기
쉬운 주제부터 고급 주제까지 차근차근 step by step
Python과 R 두 가지 언어로 제공되는 50편의 실습 코드
Q. 확률과 통계는 왜 배우나요?
ChatGPT와 같은 인공지능이 하루가 다르게 발전하면서 세상을 바꿔가고 있습니다. 아시는지요? 자연어 인공지능은 확률과 통계 모델에서 시작했다는 것을! 데이터사이언티스트가 되려면 확률과 통계는 선택이 아닌 필수입니다.
Q. 저는 비전공자인데 어느정도 수학 지식이 필요할까요?
고등학교 졸업자 또는 대학 1학년 수준의 수학 지식이면 충분합니다. 이공계 전공자 수준의 수학지식을 전제하지는 않습니다.
Q. 실습 예시는 Python과 R 두 가지 언어로 제공되는데, 어느 언어가 더 좋은가요?
각각 언어의 특장점을 살려서 실습을 진행합니다. 어느 한쪽만을 선택하셔도 충분합니다. 최근 몇년간의 추세는 Python 우세 이기때문에 이점 고려해 주시면 좋겠어요.
Q. 많은 실습 예문이 제공되는 것은 알겠는데 대신 이론이 부실하지 않나요?
절대 아닙니다! 이론 강의에서는 꼭 필요한 수식과 개념 위주로 원리를 설명합니다. 전공자도 어려운 전공서적을 읽기 전에 저희 강의를 수강해 주시면 분명히 도움이 됩니다.
Q. 선수 지식이 있나요?
이 강의에서는 Python과 R의 기초 문법에 대해서는 다루지 않습니다. 기본적인 코딩 지식과 배열, 데이터 프레임, 시각화 등의 지식이 있다면 더 이해하기 쉽습니다.
Who is this course right for?
For those who want to build a solid foundation in probability and statistics
Anyone interested in data science
Anyone who wants to build analytical and statistical modeling capabilities through coding
Need to know before starting?
Python Basic Grammar
R Basic Grammar
1,423
Learners
85
Reviews
12
Answers
4.8
Rating
7
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This is a data analysis, AI, and coding classroom created by Ruby and Teacher James.
Please show lots of interest~~ 😊 🙇♂️ 🙏
This is a data analysis, AI, and coding classroom created by Ruby and Teacher James. We appreciate your interest!~~ 😊 🙇♂️ 🙏 Ruby's Coding YouTube
This is a data analysis, AI, and coding classroom created by Ruby and Teacher James. We appreciate your interest!~~ 😊 🙇♂️ 🙏 Ruby's Coding YouTube
This is a data analysis, AI, and coding classroom created by Ruby and Teacher James. We appreciate your interest~~ 😊 🙇♂️ 🙏 Ruby's Coding YouTube
All
94 lectures ∙ (15hr 29min)
Course Materials:
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12 reviews
4.8
12 reviews
Reviews 7
∙
Average Rating 5.0
5
While studying data analysis, there weren't many statistics lectures, but this was a useful lecture. Statistics is heavily weighted in the Big Quarter or ADP exams, so I hope that you are preparing the next lecture, which will be a lecture that can be used a lot in the exam.
Thank you for your review. I will prepare well for the next lecture~~!!
Reviews 1
∙
Average Rating 5.0
5
It seems like you are explaining only the essential parts that are necessary for studying math after a long time. The curriculum is very comprehensive. It seems like you have extracted only the essential parts for each topic with appropriate depth. In particular, Markov chains and hidden Markov processes required for NLP were very useful. I liked that it was a lecture that incorporated the instructor's experience rather than a college lecture that just skimmed through the textbook.
Reviews 7
∙
Average Rating 4.0
5
It was nice to be able to see things more broadly than in any other class. I think I can study the details as I go. Thank you to the instructor.
Thank you for your review ^^
Reviews 1
∙
Average Rating 5.0
5
I am a non-major interested in data analysis and artificial intelligence. I applied for the course because probability and statistics were essential. I looked for a book that suited me, but I couldn't find it, so I applied for the course after watching the preview of this lecture. It is definitely not an easy subject, but it is easy to follow because it only covers the key points step by step. It is good because I can cool my head and check what I learned in theory by occasionally practicing coding. I highly recommend it to those who are interested in probability and statistics.
Reviews 1
∙
Average Rating 5.0
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