Becoming a Data Scientist – Curriculum via Metromap
来源:互联网 发布:remix os player mac 编辑:程序博客网 时间:2024/05/16 09:58
Data Science, Machine Learning, Big Data Analytics, Cognitive Computing …. well all of us have been avalanched with articles, skills demand info graph’s and point of views on these topics (yawn!). One thing is for sure; you cannot become a data scientist overnight. Its a journey, for sure a challenging one. But how do you go about becoming one? Where to start? When do you start seeing light at the end of the tunnel? What is the learning roadmap? What tools and techniques do I need to know? How will you know when you have achieved your goal?
Given how critical visualization is for data science, ironically I was not able to find (except for a few), pragmatic and yet visual representation of what it takes to become a data scientist. So here is my modest attempt at creating a curriculum, a learning plan that one can use in this becoming a data scientist journey. I took inspiration from the metro maps and used it to depict the learning path. I organized the overall plan progressively into the following areas / domains,
- Fundamentals
- Statistics
- Programming
- Machine Learning
- Text Mining / Natural Language Processing
- Data Visualization
- Big Data
- Data Ingestion
- Data Munging
- Toolbox
Each area / domain is represented as a “metro line”, with the stations depicting the topics you must learn / master / understand in a progressive fashion. The idea is you pick a line, catch a train and go thru all the stations (topics) till you reach the final destination (or) switch to the next line. I have progressively marked each station (line) 1 thru 10 to indicate the order in which you travel. You can use this as an individual learning plan to identify the areas you most want to develop and the acquire skills. By no means this is the end; but a solid start. Feel free to leave your comments and constructive feedback.
PS: I did not want to impose the use of any commercial tools in this plan. I have based this plan on tools/libraries available as open source for the most part. If you have access to a commercial software such as IBM SPSS or SAS Enterprise Miner, by all means go for it. The plan still holds good.
PS: I originally wanted to create an interactive visualization using D3.js or InfoVis. But wanted to get this out quickly. Maybe I will do an interactive map in the next iteration.
The author information: Linkedin
- Becoming a Data Scientist – Curriculum via Metromap
- become a data scientist
- How to become a data scientist
- A road map to become a Data Scientist(上)
- how to become a data scientist - see knowledge graph
- 译文《What everybody ought to know about a Data Scientist 》
- Becoming a Clipboard Viewer
- Becoming a Testing Expert
- Becoming a ScrumMaster
- Kaggle now has 100K data scientists, but what's a data scientist?
- codeforces 846A Curriculum Vitae
- Becoming a Software Test Expert
- Benefits of Becoming a Teacher
- 【转载】如何才是Data Scientist?
- The Data Scientist’s Toolbox
- The Data Scientist's Toolbox
- Data scientist's tool笔记
- Binding a Silverlight DataGrid to dynamic data via IDictionary
- 2014赛季中超联赛首轮山东鲁能为球迷而战
- 【项目2-日期结构体】
- SQLite的SQL语法
- Java中JButton的常用设置
- jQuery学习笔记
- Becoming a Data Scientist – Curriculum via Metromap
- 计算机应用、信息化的市场经济
- java 中string与bytes的转换总结
- 布隆过滤器
- Wildcard Matching
- StringBuilder与StringBuffer的区别
- Win7和WindowsXP怎么禁止其它帐号登录我的电脑?
- MySQL的大小写敏感性 lower_case_table_names
- -----------------res里面的drawable(ldpi、mdpi、hdpi、xhdpi、xxhdpi)