Why Join A Data Science Course in 2023
What is the relevance of Data Science courses in the current technological landscape?
What is the relevance of Data Science courses in the current technological landscape?
Every corporation nowadays requires data to manage its operations. The greatest option for storing a well-organized collection of data is a database. Furthermore, the most used computer language for data storage and retrieval in databases is SQL (Structured Query Language). It allows us to perform CRUD actions (create, read, update, and delete) on the database.
“It can be tough to leave your comfort zone and try something new, especially if you've been in the same organization and role for a long time. But, sometimes, you need that extra push to get out there and go for it. OdinSchool's Data Science Course instilled in me the courage and confidence I needed to go get a new job.”
“I used to be so disconnected from the domain of Data Science, that when I heard about Python (programming language), for the first time, I thought the instructors were referring to snakes”, in a conversation with OdinSchool, OdinGrad Nidhi Kulkarni from Hyderabad ruminates.
Data Science is one of the fastest-growing professions in the world. This interdisciplinary domain is what helps organizations, small-scale to large-scale, to unearth critical business intelligence and make informed decisions. As the world gets increasingly digital, the relevance of Data Science has also become unstoppable. Read this article to find out why you need to learn Data Science right now.
Points covered:
1. Data Science Hiring Trends at India's Premium IT Companies
2. Reasons to...
Being a Data Scientist has been a successful career choice during the last few years. Read on to know more.
As the name implies, data science is the area of study that investigates enormous volumes of information using modern tools and techniques to find unseen patterns, derive meaningful information, and make business decisions based on that information. Predictive models are built using complex machine learning algorithms in data science. The data used for analysis can come from many different sources and be presented in various formats.
Nipun Gupta from Bhopal had a very fulfilling career as a professor. But, over the course of time, he realized that to be at the forefront of the advancements in the industry and to stay a viable candidate in the job market, one needs to upskill and reskill. Nipun decided to beat his career stagnation with a career in Data Science.
Are you a budding Data Science professional? Does the thought of getting rejected by hiring managers keep you up at night? If yes, you are certainly not alone. A hiring manager goes through hundreds of Data Science profiles every day. The only way to make it to your dream job role is by making yourself stand out in the job market. This is where your Data Science portfolio steps in and saves the day.
Suppose you are working as an analyst, and your manager asks you very specific questions like “what is the current sales trend?”, “what are my customers buying?”, “is my customer buying a mobile? which is the most likely product he may buy along with it?”, “how much do we need to produce to meet the market demand?” how would you answer them?
To answer all the questions above, one needs to start with mining data. It also helps machine learning engineers in processing the data. Keep reading to...