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Introduction to Python for Programming and Data Science

The best course to learn programming! This is a good course to learn programming and improve your skills, from solid concept explanations to quizzes and homework to review, using the easy and versatile 'python'. This is a good course for anyone who wants to become a data scientist, a programmer, or use programming for repetitive tasks.

(4.5) 93 reviews

2,301 learners

  • TeamLab
Python
Big Data

Reviews from Early Learners

What you will learn!

  • Introduction to Programming

  • Introductory knowledge for computer engineering and data science

  • Python grammar, programming

  • Solving Python grammar problems through various examples

0. Publication of textbooks

This course has a published textbook based on its contents.

  • Python Programming for Data Science - yes24 , Naver


1.
Course Introduction

This lecture is the first lecture of the data science course developed by TEAMLAB and Inflearn, "Introduction to Python for Data Science." This lecture was created based on the content of the K-MOOC: Introduction to Python for Data Science (YouTube) course, which was produced with the support of the Ministry of Education. This lecture was created with the support of 249 people through crowdfunding prepared by TEAMLAB and Inflearn. We plan to develop additional lectures on the list below in the future.

  • Introduction to Python for Data Science - Main Course
  • Machnine Learning from Scratch with Python Part I
  • Machnine Learning from Scratch with Python Part II

Please also refer to the list below for existing K-MOOC courses.

Python is currently the most widely used language for data analysis, development, artificial intelligence, and office automation. Through this course, you can build a foundation for understanding how to use Python, programming concepts, and specialized lectures that will be added in the future.

Learning Objectives Helpful people
Acquire basic knowledge of basic programming language grammar and data handling. Anyone who wants to get started with programming, a beginner who wants to learn data science, anyone who wants to build a foundation before starting machine learning, anyone who is preparing for a job in the data science field


2.
Course Features

A rich curriculum consisting of lectures, quizzes, and practical exercises with certified instructors

This Python programming course is structured as a lecture-quiz-practical assignment for each chapter.
If you count 1 chapter as 1 week, it's 15 weeks of study.
Professor Seong-cheol Choi, who has experience in both corporate and academic settings and has received much support from previous K-MOOCs, and Inflearn have prepared this with great care.


3.
Why Python?

#1 most popular programming language

The grammar is concise and easy to learn. Since it is open source, there are many useful libraries.

Can be used in a variety of ways in one language!

Python is a popular language used in various fields such as programming, data analysis, and the Internet of Things. Learn basic Python and improve your skills through various advanced courses such as programming or data analysis!


4.
References

Jump to Python , by Park Eung-yong,
2014 Hello Python Programming, by Warren Sande and Carter Sande / Translated by Seungbeom Kim and Junpyo Park,
2014 Ha Yong-ho, How should we view startup data ?
2014 Choi Seong-cheol, Introduction to Programming for Industrial Engineering Part 1 (w/Python) ,
2014 Seongcheol Choi, Introduction to Programming for Industrial Engineering Part 2 (w/Python) ,
2014 Choi Seong-cheol, Introduction to Programming for Industrial Engineering Code (w/Python) ,
2014 Code Assignment Analysis Technical Support: Lablup (www.lablup.com)

5. Instructor Introduction

Choi Seong-cheol (Director of TEAMLAB )

Gam Dong-geun, Kang Nam-gu, Kang Dong-hoon, Kang Min-goo, Kang Seung-hyung, Kang Shin-hyun, Kang Jeong-mo, Kang Cheon-seong, Kyeon Eun-gyeong, Ko Sang-gyu, Ko Tae-young, Ko Hyeong-ju, Kwak Byeong-woo, Kwak Jun-gyu, Kwak Hyo-eun, Kwon Ki-woong, Kwon Su-rim, Kwon Jun-ho, Kim Kang-han, Kim Ki-beom, Kim Ki-hyun, Kim Dae-hyun, Kim Dong-soo, Kim Beom-young, Kim Sang-ho, Kim Seok, Kim Seol-hwa, Kim Seong-seon, Kim Yeong-gon, Kim Yeong-bok, Kim Wan, Kim Woo-jae, Kim Won-jun, Kim Yu-jun, Kim Jae-hoon, Kim Jong-cheol, Kim Joo-ho, Kim Jun-yeop, Kim Jun-cheol, Kim Jun-tae, Kim Ji-hoon, Kim Jin-yeong, Kim Tae-il, Kim Tae-hyung, Kim Hyun-soo, Kim Hyun-il, Kim Hyun-pyo, Kim Hyung-soo, Kim Hee-jung, Nam Goong-yeong, No Dong-heun, No Jeong-cheol, No Jin-seon, No Tae-ju, Ryu Jae-guk, Ryu Ji-hwan, Mok Jeong-hwan, Moon Jong-bae, Moon Jin-sol, Moon Jin-won, Park Kyung-hwa, Park Dong-hee, Park Du-gang, Park Min-joon, Park Seon-ho, Park Se-won, Park Soo-yeon, Park Shin-young, Park Jae-ho, Park Je-min, Park Jun-hwan, Park Jin-tae, Park Chan-jin, Park Cheol-hong, Park Tae-gyun, Park Tae-wook, Park Hye-won, Park Hong-seong, Park Hoon-beom, Park Heung-joo, Bae Yoon-seong, Bae I-hwan, Bae Jin-ui, Baek Gil-ho, Baek Sang-il, Byeong-seop Byun, Ki-yong Seo, Dong-jin Seo, Dong-hwa Seo, Yoon-hee Seo, Jae-won Seo, Min-ho Seong, Ki-chang Son, Baek-mo Son, Yu-yeon Son, Jeong-hoon Son, Min-gyu Song, Eun-jeong Song, Ji-hoon Song, Dong-soo Shin, Myeong-seok Shin, Ik-soon Shin, Jae-geun Shin, Jeong-hyeon Shin, Jin-gyu Shin, Heon-seop Shin, Byeong-hun Ahn, Jung-hee Ahn, Je-yeol Yang, Seong-woo Oh, Seung-jae Oh, Jae-woo Ok, Ji-won Woo, Seon Won, Ha-ri Won, Jae-hyeok Wi, Yeong-ho Yoo, Byeong-gil Yoon, Seok-chae Yoon, Seok-pil Yoon, Yoon Sung-hyun, Yoon Jun-seo, Yoon Jin-hwan, Lee Kyung-rok, Lee Kyung-mi, Lee Kyung-eun, Lee Ki-yong, Lee Dae-gyu, Lee Deok-gi, Lee Don-joong, Lee Min-sun, Lee Sang-yeop, Lee Seong-ju, Lee Seong-han, Lee Seong-hoon, Lee Su-hwan, Lee Seung-gyu, Lee Seung-jun, Lee Shin-ae, Lee Yeon-jun, Lee Yeong-sook, Lee Yeong-il, Lee Yong-min, Lee Yu-jeong, Lee Eun-seop, Lee Ja-ho, Lee Jae-jun, Lee Jae-hyun, Lee Jeong-yeon, Lee Jeong-ho, Lee Jong-seok, Lee Ju-woong, Lee Ju-won, Lee Ji-seon, Lee Ji-o, Lee Chang-seop, Lee Hyeong-beom, Im Se-min, Im Won-gyun, Im Jong-tae, Im Ji-hong, Im Chae-hyeon, Jang Seok-won, Jang Woo-il, Jang Woo-cheol, Jang Jun-hyeok, Jang Hyeon-jeong, Jang Hong-gi, Jeon Gyeong-hwan, Jeon Yong-jin, Jeon Jong-yeol, Jeon Jin-myeong, Jeong Gwang-yoon, Jeong Gwang-ho, Jeong Dae-hwan, Jeong Dong-ryeol, Jeong Dong-min, Jeong Seong-uk, Jeong Su-jeong, Jeong Seung-hyeon, Jeong Yeong-gyo, Jeong Yun-gi, Jeong Chan-mo, Jeong Hyang-won, Jeong Hyeon-cheol, Jo Gwang-je, Jo Min-ha, Jo Su-jeong, Jo Yeong-man, Jo Yong-jun, Jo Won-seok, Jo Jae-moon, Jo Jung-hyun, Joo Jeong-seok, Jin So-ra, Cha Dong-cheol, Cha Jin-man, Chae Ho-jin, Choi Gyeong-min, Choi Woong-sik, Choi In-bo, Choi Jeong-won, Choi Je-ho, Choi Jun-sik, Choi Han-dong, Chu Jeong-ho, Ha Jun-su, Han Bo-ram, Han Seong-uk, Han Seong-hyeon, Han Hyeong-seop, Hyun Seung-cheol, Hong Mi-na, Hong Sim-hee, Hong Jun-won, Hong Tae-hwan, Hwang Dae-seong, Hwang Eui-young, Hwang Ji-young, Hyo-ju, eric, Sunghuek Park, Lablup, Shin Jeong-gyu, TeamLab, Choi Soo-kyung, Lee Se-ri

Recommended for
these people

Who is this course right for?

  • If you want to learn data science

  • Those who want to learn programming

  • Those who are new to coding or don't know how to solve problems

  • Those who want to improve their skills through assignments

Need to know before starting?

  • Anyone!!

Hello
This is

Curriculum

All

118 lectures ∙ (16hr 9min)

Course Materials:

Lecture resources
Published: 
Last updated: 

Reviews

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93 reviews

4.5

93 reviews

  • 김동혁님의 프로필 이미지
    김동혁

    Reviews 20

    Average Rating 4.8

    5

    100% enrolled

    저는 1-2달 전쯤에 이 강의를 완료하고 장고강의까지 끝난 상태입니다. 국내에 파이썬 강의를 이보다 더 잘만든 강의는 없다라고 느꼈습니다. 왜냐하면 파이썬의 강의뿐만 아니라 숙제시스템도 엄청 잘 구축되어있습니다. 배웠으면, 써봐야 내것이 됩니다. 다른 강의들은 강의만 하고 끝내서 본인이 스스로 실습을 안하면 내것이 잘 안됩니다. 하지만 이 강의 내부에는 레포트를 원격으로 제출할 수 있고 채점하는 시스템이 구축되어 있습니다. 이 강의를 듣고 파이썬 기초 마스터가 되세요 파팅~~ 그리고 좋은 강의 제공해주신 교수님과 관계자들에게 감사드립니다. (__)

    • 윤지환님의 프로필 이미지
      윤지환

      Reviews 7

      Average Rating 4.7

      5

      50% enrolled

      강좌도 강좌지만 공부한 내용을 가지고 과제를 풀어나가는게 참 재미있네요 끝까지 달려 봅시다!!

      • 유근지 yoo님의 프로필 이미지
        유근지 yoo

        Reviews 5

        Average Rating 4.0

        3

        88% enrolled

        입문 보다는 중급이상일것 같습니다. 채점때문인건지 프로그래밍 입문자가 아니면 초반부터 나오는 def는 좀 난감할 것 같습니다. 구성자체를 초반에는 jupyter notebook이나 ipython 으로 기본 문법 및 문제해결을 좀 키우다가 def로 넘어가면 좀더 부드럽게 넘어갈 것 같습니다.

        • 정영욱님의 프로필 이미지
          정영욱

          Reviews 6

          Average Rating 5.0

          5

          100% enrolled

          정말 많은 시간 투자하여 강의 만드신 것 같아요! 자세한 설명들 감동입니다~

          • 권기민님의 프로필 이미지
            권기민

            Reviews 1

            Average Rating 5.0

            5

            100% enrolled

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