10 answers
11
Asked 970 views

How can I start in Data Science?

I haven’t got any technical experience. I studied business administration and management and a master of management and technology of business process. It would be a great achivement for me to learn and understand this field. #business #computer-science #data #science #python #neural #networks

business science computer-science python data networks neural
Answer This

+25 Karma if successful
From: You
To: Friend
Subject: Career question for you
11

10 answers

1
Updated
Share a link to this answer
Share a link to this answer

Abhishek’s Answer

Data science is a broad field and data scientists usually come from various backgrounds such as business, physics, math, computer science etc. Make sure you learn basic and advanced statistics coupled with programming languages such as Python and R. This should give you a solid foundation in Data science.


- Gain experience in the field you intend to work in (ex: healthcare, physics, business)

- Learn basic and advanced statistics coupled with programming languages such as Python and R

- Kaggle is a great way to gain hands-on experience

Abhishek recommends the following next steps:

Gain experience in the field you intend to work in (ex: healthcare, physics, business)
Learn basic and advanced statistics coupled with programming languages such as Python and R
Kaggle is a great way to gain hands-on experience
1
0
Updated
Share a link to this answer
Share a link to this answer

Aiswarya’s Answer

Listing down the starter kit for Data Science :
Maths — 3Blue1Brown (https://www.youtube.com/channel/UCYO_jab_esuFRV4b17AJtAw)
Machine Learning — Andrew Ng, Coursera (https://www.coursera.org/learn/machine-learning)
Programming — Python for Data Science and Machine Learning (https://www.udemy.com/course/python-for-data-science-and-machine-learning-bootcamp/)
Statistics — Elements of Statistical Learning (https://web.stanford.edu/~hastie/Papers/ESLII.pdf)

A strong grasp of these techniques and practice (a lot of practice), will help you kick-start your career in data science.
0
0
Updated
Share a link to this answer
Share a link to this answer

Nick’s Answer

In addition to the technical aspects of data science that have been excellently covered in the other answers, make sure to also develop an understanding on how to approach business problems and project requirements. This will help bridge the gap between data language skills and the practical application of them.
0
0
Updated
Share a link to this answer
Share a link to this answer

Firoz’s Answer

Areas of understanding or skills that can be very helpful include:
-- Data Visualization
-- Tableau
-- SAS
-- SQL
-- Foundational understanding of data modeling
-- Understanding of how data flows from systems to landing areas to data use layers
-- Hadoop
-- Impala
-- Python
0
0
Updated
Share a link to this answer
Share a link to this answer

Sean’s Answer

Data Science is a very broad field and may cover difference techniques in difference companies/circumstances. From your hashtags I am assuming you wanted to learning Machine Learning.

Nowadays there are many useful beginner ML classes online you can find. The most famous one is the one from Andrew Ng on Coursera https://www.coursera.org/learn/machine-learning. It covers the basic of ML.

After getting basic ideas, you can start playing with different Python package on public datasets. You can check out Kaggle competitions, find simple problems to solve, and see how other people solve it in the Kaggle forum. Learning by doing is the way I found most effective. :)

Sean recommends the following next steps:

Take https://www.coursera.org/learn/machine-learning
Play with public datasets
0
0
Updated
Share a link to this answer
Share a link to this answer

Michele’s Answer

I would do some research. Here in the US, Data Science is a rather saturated market right now with many people graduating and competing on this area so companies are specific about what they are looking for. You might look broader at Analytics types of roles where you can use your education background which might be a bit easier initially.
0
0
Updated
Share a link to this answer
Share a link to this answer

Varsha’s Answer

You can start with high school statistics and start developing some programming and logical skills.Basic statistics can help you develop problem solving and analytical skills.
0
0
Updated
Share a link to this answer
Share a link to this answer

Hicham’s Answer

You can start with some online courses and watching some dedicated youtube channel. Here is some link to start with :

https://www.youtube.com/watch?time_continue=1&v=X3paOmcrTjQ

https://www.youtube.com/watch?time_continue=4&v=PPLop4L2eGk

https://www.youtube.com/watch?time_continue=750&v=FbxTVRfQFuI

https://www.youtube.com/watch?time_continue=130&v=AoqBwMc9_yY

Some notion in mathematics, statistics, probability wil help you in the transition.

Let me know if you want yo go further in data science and will recommend some more advaced courses

Hicham recommends the following next steps:

Take some some Moocs from coursera and EDX and earn some certifications
Select an application domaine : marketing, health, biostatitics ...
Try to solve some real live problems using open/public data
0
0
Updated
Share a link to this answer
Share a link to this answer

Sulli’s Answer

Main point of 'data science' is handling huge size of data which cannot be easily summarized by light tools (like excel).
To do this, you have to get used to at least one kind of programming tool or language.
It can be a SQL, R, Python, C etc.
You can learn these kind of tools easily in various websites.

Also, there exists various career paths inside the data science track.
You can be a data scientist who are specialized in business analyzing, data visualization or AI model development.
So before decide what technical skills you want to learn and what area you will focus, I recommend you to research about data-related industry needs and trends of data field.
0
0
Updated
Share a link to this answer
Share a link to this answer

Saquib’s Answer

Step 0: Figure out what you need to learn

Step 1: Get comfortable with Python

Step 2: Learn data analysis, manipulation, and visualization with pandas

Step 3: Learn machine learning with scikit-learn

Step 4: Understand machine learning in more depth

Step 5: Keep learning and practicing

Bonus: Join Data School (for free!)
0