How You Can Become a Data Scientist without Degree
Becoming a data scientist with a degree is a challenge in itself, but becoming one without a degree is even more of a challenge as you cannot learn all the skills of a data scientist. Learning certain resources or something.
Now crucial skills for example communication. Cannot be learnt online, some certain skills like these are which the degree really helps you develop. There are some online education communities offer free data science online course.
How to Enhance a Data Scientist Without a Degree
Learning data science takes a lot of time, patience and a lot of effort but is worth it at the end for sure. To become a data scientist what all you’re gonna do is:
10 Points To Consider For Becoming The Data Scientist
You gotta have a very good understanding of maths, probability, statistics and algebra and for all these, there’s a book called practical statistic s for data scientists which is highly recommended for something like this.
Second is you gotta learn the general analytical skills using Excel and SQL. Here you will learn things like database management, reporting, procreation, business KPI and data visualizations.
To Learn all these, there’s a book called data analysis using SQL and excel the second edition and for courses, one of them called gain well-rounded analysis skills by Microsoft.
This one is actually a three program course and if you read about each of the programs one of them is called querying data with transactional SQL and it’s going to teach you using SQL for analytics and the course is free but does buy the certificate as buying it will help you get a good job. Next up for the program is analyzing and visualizing data with Excel and the third one is called data analysis using excel.
Now you gotta learn python or R and then how to run the machine using those tools. For machine learning, you should opt for some of the most widely used libraries. The first one is Numpy – Numerical python, for all your calculations and maths. The next one is pandas- for data manipulation and data analytics.
The next two are matplolib and Sybil-help when you’re performing your exploratory data analysis in doing visualizations and then once you master in these, you should preferably moving into scalar which is the one you should use for your machine learning models following the machine learning process.
This one has tons of machine learning models for using in terms of books but using the book called, hands-on machine learning scikit, Keras and TensorFlow. This is provided by Ellie and Iran and for courses is called learn data science by doing data science and is provided by the University of San Diego and in this is actually four courses. And this is going to teach you a lot of machinery and it may get you started with using it.
Next up you gotta learn is visualization tools like tableau power bi and click cells. these tools are the tools you’re going to use to communicate your visualization back to the business or to deploy your machine learning models.
Next to us is having a basic knowledge of cloud tools, the reason for its importance is because all organizations.
Nowadays are migrating their data from on-premise solutions into cloud solutions. There are three main cloud solution providers which are the azure, AWS and TCP.
After finishing learning all the tools and processes, you will need to spend time to improve your communication skills and these skills are actually super challenging to learn just online as they’re best learnt when you interact and collaborate with people and work in teams, these skills are crucial in this field as you’re gonna use the skill to explain how to use your model and eventually it is gonna add value to you.
These skills will also be helpful to you while answering to the technical or not questions of the interviewer while giving an interview. For these, the book used should be communication skills training which seems to be a practical guide to improving your social intelligence, presentation and public speaking and when coming to courses, the business communications by the University of British Columbia are very useful and are gonna help you communicate effect effectively.
Also, you gotta learn how to create insights for effective storytelling as its gonna add value to your business, for this the course has to be, analytics storytelling for impact provided by Microsoft which tells you the Way to apply storytelling principles to your analytics world to add value to the business.
Now you’ll have to create a GitHub portfolio and document for all the data project or data analytics or machine learning etc. it is going to be used in your interviews to demonstrate all the knowledge you have in data science.
The last thing is that you should have a very strong data scientist branded LinkedIn profile that demonstrates that you have a lot of knowledge around data science and machine learning.