what should I learn to be a data scientist?
I want to be a data scientist, what online courses should I take ? #datascience
6 answers
Aroquiamarie Kavitha’s Answer
1. Basic math for data science (Linear algebra, elementary calculus and statistics)
2. Writing code with basic programming constructs (either python or R)
3. Data wrangling skills (use of Database technologies like SQL to handle larger data that doesn't fit in spreadsheet)
4. Hands on mindset to play around with different data tools / softwares on linux based systems.
5. Understanding the nature of how the data is created and the business function of the data
6. Storytelling with data (talking different stakeholders of the business on the findings and observations about the data)
Good to have:
1. Basic knowledge of handling data in cloud systems like AWS, Google cloud, Azure.
Basic mini courses
kaggle courses (they have a curriculum from beginner to intermediate level)
https://www.kaggle.com/learn [kaggle.com]
If you have programming experience and looking for an experiential learning with more hands activities via programming try fastai
https://course18.fast.ai/ml.html [course18.fast.ai]
If you have good foundation in high school math and prefer the traditional learning methodology, Stanford CS229 Machine learning is a good place to start
https://www.youtube.com/playlist?list=PLoROMvodv4rMiGQp3WXShtMGgzqpfVfbU [youtube.com]
Once done you can start working on portfolio projects of interests and showcasing them in your resume as suggested in the recommended courses. Often try to solve real world problems by taking part in kaggle competitions.
Sejal’s Answer
- Python: One of the points that makes a data scientist different from a data analyst is the ability to deep dive into machine learning models. Python is the most commonly used programming language for building these models. Also, a few specific topics like Pandas, NumPy under python are used extensively to analyze data.
- Extensive study of data analytics topics: Start from the basics like small concepts of data analysis, manipulation, data correction, and then moving into the data modeling topic. Recommended book: An Introduction to Statistical Learning: with Applications in R
Thomas’s Answer
- Statistics and mathematics: Data science is heavily reliant on statistics and math, so it's important to have a strong foundation in these areas.
- Programming languages: It's essential to be able to write code in order to manipulate and analyze data. Python is a popular language for data science, but there are many others that can be used as well.
- Database management: A large part of data science involves working with and managing large datasets. Mastery of database management tools and
Fabio’s Answer
Hello Chong G.
I am not a data scientist, but I think I can give you some advice on this. Nowadays, an increasing number of professions are requiring analytics capabilities.
There are some core things you should learn to handle great amount of data, like:
Relational Database concepts;
SQL - Computer language for creating and managing databases;
Excel;
Programing languages such as C, VBA, R...
You should also consider learning how to display the data in an organized way and Power BI / Think-Cell are great for that
There are several tutorials around the internet about those topics and also focused courses. I personally recommend the latter, because it is easier to progress through the topics.
Hope my advice was helpful to you!
karthik’s Answer
Many job postings list advanced degrees as requirements for data-related positions. Sometimes, that’s non-negotiable, but as demand outstrips supply—and given the often specialized, highly technical nature of the work—the proof is increasingly in the pudding. That is, data skills often outweigh mere credentialism. What’s most important to hiring managers is an ability to demonstrate mastery of the subject in some way, and it’s increasingly understood that this demonstration doesn’t have to follow traditional channels.
In the end, there’s no single path toward becoming a Data Analyst, and that’s good news if you’re hoping to land a data analysis role. Because Data Analysts can work across many different industries, may be generalists or highly specialized, and often play an interdisciplinary role in a company, even job titles in data analysis can be quite varied
Rafael’s Answer
You should search for Algorithm videos. Usually when studying data, you would need to know about databases structure, analytics skills, and some other logics. Another thing you could do would be start analyzing some small real cases like how long does it take to go from your house to the supermarket and what you could do to reduce the time? or how often do you drink water (time gap between each occurence). How could you track that? and how could you improve it? is it good?
these are a few examples on how you could analyze stuff.