Sequential Learning for a Data Science Career in 2020
Data is considered the new fuel to power businesses globally in the modern day. Various studies conducted across the world have already shown that Big data, AI, and Machine Learning will be the three key technologies to rule the world in the times to come.
And is therefore, quite evident, that students and professionals with any kind of data certifications under their belt will be the top earners across industry verticals. Especially, in the 2020s, they will be among the most-valued people in the corporate sector.
What is meant by Data Science in General?
It involves collection of digital data from varied online sources, mostly consumer data, and the analysis of the same to extract highly-useful pieces of information that can help a business grow exponentially in a short period of time.
This data to be analysed could be in any form, whether images, text, videos, numbers, etc. The extracted useful information out of this data can help engineers to automate a machine to perform a set pattern of tasks. Moreover, this critically-useful extracted information can help predict future market and business trends.
Why Go for Data Science Certifications in the First Place?
Data science career is the most rewarding in the current times with the highest pay in the job market, and is expected to be even more lucrative, in terms of pay package and remunerations during the entire 2020s.
A data science qualification at the moment is a kind of jewel on your head shining bright. One would be surprised to know that currently the demand for data scientists globally, exceeds the supply by more than 50%.
Relevance of Data Science in 2020 and Beyond
The world we live in is full of data. All one needs, is to use this valuable data to extract information. Having gone digital, people across the globe are leaving their footprints in terms of choices, preferences, likes, and dislikes, etc. over the web, mostly on social media. And, this data is what businesses need in order to target their potential customers.
Such data can be highly useful to businesses to get an idea regarding the below provided business aspects:
· reduce costs
· visualize trends
· extend business to different demographics
· launch new products and services
Let’s Now Get into Learning Data Science Step-By-Step from Scratch
The Learning Plan
Here is a step-by-step learning plan for students as well as professionals, entailed level-wise. There are four major levels in which the learning course is divided.
Whether you are at a “beginner’s level”, “intermediate level” or “advanced level” in terms of your expertise in data science, this learning mechanism will make it extremely easy to learn the subject as a whole.
👉TECHNICAL KNOWLEDGE & RELATED SKILLS
Starting with technical skills would be the best way to start with learning data science as a subject. It will help establish a base in understanding the algorithms involved, and the related mathematics.
When it comes to obtaining data science qualifications as a student or a professional, the first step is to learn the language — Python. It is the most popular language to create and develop algorithms in data science. Added to that, there are huge libraries in data science available in Python, collectively created by a number of developers located across the globe.
Besides, one must also learn R programming language, as it is what helps the most in data analysis.
a) Python Fundamentals
Those aspiring for a data science career, before starting on solving data science related problems, must understand the fundamentals of Python. One can opt for DASCA data-science courses and certifications that offer the learner world-class study-material, and globally-recognized certifications in different branches of data science.
b) Using Python for Data Analytics
Having learnt the basics of Python, one can advance towards using the said language for much critical data-analysis.
c) Utilising Python for Machine Learning
There are a number of free resources online to learn the basics of ML. Just take care that whatever course you take, it must involve scikit-learn, the most popular Python Library for machine learning and data science.
Data science qualifications and certifications that ensure your expertise in Machine Learning are some of the most “in-demand” skills in the corporate world.
d) Learning SQL Programming Language
Next on the list to learn, in terms of developing and taking forward your data science career, should be the much important — SQL, a programming language for handling data stored in a Database Management System.
e) Language R — for Statistical Computing
One should not only rely on Python when it comes to data analysis. Learning R will be an added advantage, as it will allow you to gain advanced knowledge in statistical computing, a vital branch of data science. And, to further better their skills in data science, one must learn this language religiously.
👉Mathematics Involved in Varied Data Science Qualifications
Mathematics and statistics are the two vital aspects of data science in general. One simply cannot avoid the mathematics of data science, if he really wants to excel in the subject.
Calculus
Calculus is an inseparable part of any machine learning algorithm, and hence serves as a mandatory requirement in order to attain a data science certification. Having a good grasp of the topic can take you miles in your career as a data scientist.
Here is the list of topics you need to study under Calculus:
Derivatives
· Geometric definition
· Nonlinear function
· Derivative of a function
Chain Rule
· Derivatives of composite functions
· Composite functions
· Multiple functions
Gradients
· Integrals
· Directional derivatives
· Partial derivatives
Linear Algebra:
Linear algebra is another branch of mathematics you should be well-versed in, if you want to make your career in data science and analytics.
The knowledge of linear algebra comes handy in managing the two most crucial verticals of data science, i.e. — Artificial Intelligence, and Machine Learning.
Here the varied topics under linear algebra that you will need to study:
Vectors and spaces
· Linear dependence and independence
· Vectors
· The vector dot and cross product
· Linear combinations
Matrix transformations
· Linear transformations
· Multiplication of a matrix
· Inverse function
· Transpose of a matrix
Statistics: To get a hold on the best data science certifications of 2020, one would need to excel in this department of mathematics, namely — Statistics. This branch of mathematics in particular, focuses on sorting and utilising data for extraction of maximum value out of it.
Here are the list of topics under Statistics that one would need to study:
Descriptive Statistics
· Dependence measure
· Central tendency
· Types of distribution
· Summarization of data
Experiment Design
· Hypothesis testing
· Probability
· Sampling
· Significance Testing
· Randomness
👉Machine Learning
Scoring a data science certification in 2020 would certainly require you to gain an expertise in machine learning.
Here are the three major technical aspects of ML that you should learn in order to attain expertise in the same:
· Inference about slope
· Regression
· Classification
👉Hands-On Experience or Practical Knowledge
After going through the above stated learning process, now you are ready to try your hands on solving some real-life data science problems.
You are certainly ready to apply for a globally-recognized data science certification, and attain it, by showcasing your skills as a data science enthusiast while performing in the certification exam.
Ending Thoughts
If you are looking for a rewarding career in data science in 2020, or even beyond 2020s, this is the right time to grab a certification in data analytics. It will not only help you gain an increased employability, but also a highly-rewarding life and career sustainability.
Data scientists have never been at this level of “demand” in the market, as is, in the present times. So, don’t wait opting for data science as a career, and start learning today to hold a related certification in the immediate future!
