Hello there folks it’s admin here from ADMEC Multimedia Institute and today when I was working on something, one of our old web design course students called and asked if he can switch career from Web Designing to Data Science. I tried to clear all of his doubts and he decided to give it a try. In this article I am going to do the same explanation: can a web designer move to data science.
In recent years the Data Science industry has grown a lot and will continue to do in upcoming years.
The Analytics Industry accounts for about 21% of the total IT Industry.
At first it was limited to finance and banking but now it widened its range everywhere.
What is Data Science?
Now if you are looking for the answer for this question: can a web designer move to data science then it is important to understand about this field first.
It includes operations of building a predictive model by using machine learning algorithms. We use it to record, store and analyze the data to get meaningful information and make better business decisions based on this data.
Why is it used?
Data Science is simply used to avoid making a bad decision by using the data and predict the outcome of the decision before even making it.
Say you have an e-commerce site with the help of Data Science you are able to tell what your customers want and they search the most on your site. What are competitors doing? This will help in increasing your business even further.
Applications of Data Science
- Health Sectors
- Managing Resources at Bank
- Fraud Detection
- Gaming Industry
- Recommendation System
What Data Scientist Does?
- Questioning
- Collecting
- Scrubbing
- Feeding
- Preparing
How is Data Science used?
The problem
Before starting you need to know what is the problem, what are you trying to achieve. Ask the correct questions and if you are getting broken or irrelevant input from the client side try to get a better view first.
Say you want to open a store so the first thing is
- Who are the customers,
- Will they be able to afford it,
- Why will they buy your product,
- Chances of them buying it again,
- What are your competitors how are they performing,
- What’s the time to establish a good reputation to kick start a good amount product sale,
- What will be losses if you don’t reach the target sales target
Clarify before continuing to the next step this one is the most important, if you get this wrong you get everything wrong.
Data
Got the problem let’s find a solution for doing this. You need the data. In this step we decide what type of data we need and basically how to get that data. There various ways to get the desired data
- querying internal databases
- purchasing external datasets
- CRM tools
This will take nearly 20% of the total time given for the task.
Cleansing
So we have the raw data but remember it might be possible and is true in most cases that this data has errors, null, or empty values. Now it’s time to go through each value and check for errors to make work easier during analysis. Check for following error before proceeding
- Null, Empty values
- Corrupted values
- Currency differences
- Time Zone Differences
- Date Errors
Go through every row and column and remove any irregularities. In simple words remove what you don’t need, reorganize everything and avoid any and all unnecessary repetition.
Exploration
Data is organized and ready to be used. All you now have to do is use your thinking skills to get lots of ideas on how to use this data to get better insights of the problem we had. Not all the ideas are going to cut it. Look for a pattern and test ideas.
Use data visualisation techniques, charts and graphs to get a better chance of finding that pattern.
Analysis
In this process you are going to use every single at your arsenal, crunch the data and get your results.
Say you are trying to get figures on what will happen if you didn’t meet the sales requirements,
You can create predictive models to compare where you need to cut the cost.
If all the earlier steps were taken correctly this will yield results.
Explanation
This one is important because there will be some who may not like your solution or won’t believe you for the outcome you are suggesting or solution. You have to explain everything very properly and thoroughly about the consequences if the action is taken or ignored.
If you have read it till you are very much certain about career switching huh so let’s see how are you going to learn the technologies required to be a data scientist.
What you need to know before starting career into Data Science?
Programming Languages
You can choose from Python, R, and Java. Python and R are preferred languages since they have lots of libraries and it will be easier to learn.
Machine Learning
These are the algorithms used when solving any problem.
- Regression
- Classification
- Deep Learning
- Clustering
- Reinforcement Learning
IDE
These are software on which basically you do all the coding work
- Pycharm
- Jupyter
- R Studio (only for R)
- VS Code
- Spider
Web Scraping
This is the process in which we acquire the data by using a particular library to get this done like
- Requests
- Beautiful Soup
- Lxml
- Selenium
- Scrapy
- URL Lib
Maths and Data Visualization
You need be very good at maths if you want to do this skills you’ll need for becoming a data scientists are
- Statistics
- Linear Algebra
- Differential Calculus
Another important point is how are you going to visualize the data? There are various libraries that can be used here
- Tableau
- Power BI
- Seaborn
- Matplotlib
- Pygal
- Bokeh
Job Opportunities and Roles in Data Science
There is a major hike in job vacancies related to Data Science and will continue to grow more. There are various job roles in Data Science
- Data Scientist
- Machine Learning Engineer
- Data Consultant
- Data Analyst
At the end, let me clear your final doubts related to question: can a web designer move to data science. I think a web designer can go for statistical analysis (SA) as it only covers R, and Python, they resemble so much with other programming languages.
Look if you think you can do this go for it no problem but remember this will be a complete new field and all the experience you have for your previous job will count for nothing. Both careers are a lot different from each other. Ultimately, it’s your decision to choose wisely. Don’t change career out of fear.
Interested in Learning Data Science
If you are serious about learning Data Science look no further we are the best education centre in Delhi. Check out our data analytics courses and get started.
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- 06 months Master Diploma – Join Data Analytics course in Delhi at ADMEC
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