7 answers
Taeseong
Student
Seoul, South Korea
1
Question
7 answers
Vijayanand Ponukumati
Engineering
3
Answers
San Jose, California
Updated
Vijayanand’s Answer
All the answers by Heine & Mingze are relevant. I would also add that if you are in school, focusing on Math - Probability and Statistics and Linear Algebra, Vector Algebra is critical for being a good data scientist. Ofcourse, the programs on coursera.org are then building on top of that.
Good luck. this is a hot field, so the industry has a lot of demand for good data scientists.
Mingze Li
Senior Manager - Global Fraud at American Express
1
Answer
Phoenix, Arizona
Updated
Mingze’s Answer
Hi Taeseong, I am glad you are looking to learn data science since it has become a skill in demand. I have found the answer here on quora very true. I hope it will help you: https://qr.ae/TUfzd3
Mingze recommends the following next steps:
Bijan Shokrollahi
Software Consulting Engineer
2
Answers
San Francisco, California
Updated
Bijan’s Answer
Hi Taeseong,
Data Science is very much an art of story telling. You need to be proficient in the technical side of Data Science ie getting familiar with R & Python, leveraging modules like pandas, matplotlib, etc. but also you need to tell the story of the data to non-technical audience and c level suite. Like others have said, don't underestimate the math side of things which are critical. I would recommend leveraging any free resources to develop your skills. Elon Musk has said that you can learn anything you want for free. There is a significant amount of information on the internet.
--Bijan
Data Science is very much an art of story telling. You need to be proficient in the technical side of Data Science ie getting familiar with R & Python, leveraging modules like pandas, matplotlib, etc. but also you need to tell the story of the data to non-technical audience and c level suite. Like others have said, don't underestimate the math side of things which are critical. I would recommend leveraging any free resources to develop your skills. Elon Musk has said that you can learn anything you want for free. There is a significant amount of information on the internet.
--Bijan
Heine Melo
Software Architect
7
Answers
Mexico City, Mexico
Updated
Heine’s Answer
There are some very good courses from Coursera presented by universities like:
- Arizona State University
- Johns Hopkins University
- University of Illinois
- University of London
https://www.coursera.org/browse/data-science
Some of those trainings you can learn for free.
Edx has some very good trainings also from: Microsoft, IBM, MIT, Harvard.
https://www.edx.org/course/subject/data-science
I recommend you to check the content and the feedbacks. With that you can filter what is best for you.
Yubing Sun
19
Answers
New York, New York
Updated
Yubing’s Answer
There are quite a bit online resource where you can learn data science related skills.
For R/Python/SQL, I would recommend you go to DataCamp and take some courses there.
For Machine learning, you can register Machine Learning by Andrew Ng, which will give you a great overview on machine learning techniques.
Certainly, you will find a lot of tutorials when you search data science courses online.
For R/Python/SQL, I would recommend you go to DataCamp and take some courses there.
For Machine learning, you can register Machine Learning by Andrew Ng, which will give you a great overview on machine learning techniques.
Certainly, you will find a lot of tutorials when you search data science courses online.
Yi Xu
12
Answers
Updated
Yi’s Answer
there are some math skills it's better you acquire in school for understanding AI, so if it is possible, focus on them in your math class, they are basically:
Linear algebra (essential to understanding most ML/AI approaches) Basic differential calculus (with a bit of multi-variable calculus) Coordinate transformation and non-linear transformations (key ideas in ML/AI)
obviously you need programming skills, Python is still the most popular one in this Data science world, but might not be the case when you started to work on this field. so any language will do, just learn the logic and fundamentals well. l you will be able to quickly pick up new languages if you do.
and then if you want to be a data scientist, only after master these math and programming skills, you can start with classes in coursera - I would recommend Andrew Ng's intruduction to machine learning
Linear algebra (essential to understanding most ML/AI approaches) Basic differential calculus (with a bit of multi-variable calculus) Coordinate transformation and non-linear transformations (key ideas in ML/AI)
obviously you need programming skills, Python is still the most popular one in this Data science world, but might not be the case when you started to work on this field. so any language will do, just learn the logic and fundamentals well. l you will be able to quickly pick up new languages if you do.
and then if you want to be a data scientist, only after master these math and programming skills, you can start with classes in coursera - I would recommend Andrew Ng's intruduction to machine learning
Christopher Mok
Data Scientist
2
Answers
Singapore
Updated
Christopher’s Answer
It helps if you're majoring in a relevant course such as Computer Science, Data Science, or anything STEM related so that you can have a solid foundation in Mathematics. I only have a bachelor's degree in Economics so I have grasped a decent foundation in maths, statistics and regression analysis which is good enough for you to land an internship.
Other than the academic foundation taught in school, you should actively search for online courses (Coursera, linkedin-learning or youtube; I highly recommend youtube actually) to have an understanding in Machine Learning. I recommend the youtube channel called StatQuest as he explains statistical and machine learning model concepts very detailed yet in an intuitive manner. Watching youtube videos help with the intuition and motivation for machine learning, but if you want to have a deep understanding of how the maths work, I recommend taking the course Machine Learning by Andrew Ng.
Once you acquired some level of theory, you should have some experience in programming. I personally recommend learning Python as your first programming language as it is fairly simple to learn. I will do this iteratively, first learn the basic programming concepts like for loops, dictionary, functions etc. Try out some mini projects along the way to practice what you learn. Once you think you have known enough (able to google your way through), start learning data science modules (numpy, pandas, matplotlib) which are essentially the core libraries used by Data Scientists. There are fantastic tutorials in youtube so following them works just fine. Once you know enough of programming, do some projects relating to data science so you're comfortable with the syntax. Kaggle is a great place to practice what you learn on ready-made datasets.
With about 3-6months of doing this, you should be qualified enough to apply for your first internship. The real learning starts when you experience an internship and hopefully, your career as a data scientist will kick off from there. Most importantly, never stop learning. You will soon realize that the most important skill you need to have is to know how to read articles and know how to google.
Other than the academic foundation taught in school, you should actively search for online courses (Coursera, linkedin-learning or youtube; I highly recommend youtube actually) to have an understanding in Machine Learning. I recommend the youtube channel called StatQuest as he explains statistical and machine learning model concepts very detailed yet in an intuitive manner. Watching youtube videos help with the intuition and motivation for machine learning, but if you want to have a deep understanding of how the maths work, I recommend taking the course Machine Learning by Andrew Ng.
Once you acquired some level of theory, you should have some experience in programming. I personally recommend learning Python as your first programming language as it is fairly simple to learn. I will do this iteratively, first learn the basic programming concepts like for loops, dictionary, functions etc. Try out some mini projects along the way to practice what you learn. Once you think you have known enough (able to google your way through), start learning data science modules (numpy, pandas, matplotlib) which are essentially the core libraries used by Data Scientists. There are fantastic tutorials in youtube so following them works just fine. Once you know enough of programming, do some projects relating to data science so you're comfortable with the syntax. Kaggle is a great place to practice what you learn on ready-made datasets.
With about 3-6months of doing this, you should be qualified enough to apply for your first internship. The real learning starts when you experience an internship and hopefully, your career as a data scientist will kick off from there. Most importantly, never stop learning. You will soon realize that the most important skill you need to have is to know how to read articles and know how to google.