One major characteristic of the information age is just as the name suggests – there is a lot of information at the disposal of a user, to an extent that a lack of knowledge on a particular subject such as trending topics would be considered blatant ignorance. The opportunity to individually equip oneself with skills is achievable through online videos such as recordings of live Virtual classes on Introduction to Python Programming or online course platforms like Coursera. Clearly Learning has been simplified to the touch or click of a button.
Inarguably, exposing oneself to endless information available on the Internet and platforms such as our 4IR Club is necessary as it allows you to keep re-engineering and re-sharpening your skills as per the latest market trends. You remain at an enviable distance ahead of the business curve having soft skills you can easily acquire Certified Data Science Programs. Yet even so, becoming an expert is not a walk in the park. Just like any other hard-earned deal, developing a desirable maturity in the programming field will need your individual effort and proper guidance from a certified instructor.
But How Fast Can One Become a Data Scientist?
1.It will take time
While it is easy to fancy getting equipped with programming, machine learning or data science skills fast enough to make us the next employable demigod, learning these ropes takes a considerable amount of time, not just the average day. Our Intermediate Data Science Program for instance runs for approximately 16 weeks. After attending the full sessions and successfully mastering the programming languages such as Python or R, you have to keep practicing for a while to learn it well especially if they are your first languages.
2.Be realistic with your expectations
You probably feel the pressure of the need to meet the already growing business demand of the need for relevant skills needed for a digital economy. Organisations have dramatically transformed their skillset requirement and you feel the need to reskill. Do not opt to drown yourself in endless online tutorials and books on machine learning.
It could probably take you 2 months to learn the essential rules and procedures of python programming and another 3 months of practice using Kaggle datasets. Gaining the theoretical knowledge of basic machine learning can possibly happen in a week but getting a hang of it in practical applications will take a while.
3. Enroll in an institution
The Internet is a sea of data at our disposal. Thousands of online tutors bombard tailored ads, each recommending programs they think would give you a market edge. How do you settle on the appropriate one? Ernest Musyoki, one of our Data Science coaches at Predictive Lab mentions how self-taught programs from the Internet could be unstructured, thus proving less beneficial for someone who would genuinely want to learn programming. Certified institutions, such as Predictive Lab that has been approved by National Industrial Training Authority (NITA) to be a training provider for Data Science offers should be top on your list as it offers more synthesized content, tailored for individual needs.
“In this age we have too many resources on the internet that can prove a hard time learning Data Science and are confusing for a first-time learner. I would prefer they enroll to an institution where they’d get proper guidance from certified coaches,” said Ernest.
4.Understand your need
Jumping over to the next advertised machine learning course will not properly equip you for the job market. Take time to analyse the skill gap you need filled, do enough research on how you can bridge that gap and finally find out what available institution will help you with your specific pain point.
At Predictive Analytics, while our Introductory to Data Science programs remain open for first- time Data Science learners, we often receive applicants who would want to gain specific analytical skills in different professional verticals like Supply Chain, Human Resource, Retail and the likes. Before enrolling students to any of our programs, Predictive Analytics team usually hold discussions with their potential students so as to be able to understand their needs before recommending them an appropriate Data Science Course that would equip them with the skillset they need.
What you can learn in such a short span of time
1.Polish your excel skills some more : The basic excel skills of creating tabulating, creating graphs are not enough. You will need to advance, if you intend to be close to a Data Science guru. Learn some advanced techniques like v-lookup, pivot table, Macros and visual basic. There are a lot of data analyst roles from our jobs platform that want advanced excel skills.
2.Learn a good data visualization tool like Tableau which will allow you make complex visualizations with a simple drag and drop. You don’t have to write any programming logic or any code.
3.Learn SQL: Learning SQL can be easier than learning a programming language since the queries are just like a regular language which makes it easy to grasp. Moreover it is an invaluable skill in the job market as I usually meet so many people in different conferences who are working as SQL developers for the last 10 years.
Becoming better at programming depends on your approach. Generally, it takes about 3 to 6 months to learn the basics of coding but you can master the basics either faster or slower depending on your pace. Be an avid reader of articles such as our blogs, E- books, or even subscribe to our newsletter to stay updated and get some tips.
Another great way of growing professionally is to frequently attend our data science meetups, lab guests, bootcamps and conferences. Aside from building your skills, this networking will help you learn about new developments there are in Artificial Intelligence and the latest Business Intelligence Apps in the market.
Above all, constantly learn what works and what doesn’t as this will help keep you afloat .