The word has already spread that AI is the next big thing and almost all jobs across sectors and industries are going to be touched upon by AI and ML. What looked like a technology with some big disadvantages and disliked for stealing people’s jobs, AI and ML have groomed themselves to be a technology that we can’t do without.
People are now inclined to learn and upgrade their skillsets to adopt AI, businesses want to hire people who are well versed to work with artificial intelligence. Data science is trending and the best part is that it is not restricted to engineering backroad students only. Its is in demand in management, technology, medicine, and more.
Data science is the study of using a scientific approach to draw meaning and insights from data.
It is the process of using algorithms, methods and systems to gather knowledge and insights from structured and unstructured data. It combines advanced analytics and machine learning in predict ing and optimizing business outcomes.
So, what does it take to be a data scientist?
Let’s see what experts believe is required for one to be a data scientist. According to Catherine
Step-1 Ask the right questions
Questions such as
- Am I intrigued by statistics and programming?
- Am I willing to constantly upskill?
- Do I really enjoy solving problems?
- If data science wasn’t this popular and lucrative, would I still go for it?
Step-2 Fulfill Data Science prerequisites
There are both technical and non technical skillsets required.
The technical skills mainly include:
- Mathematics, statistics, and computer science
- Languages like Python and Scala
- SQL and NoSQL databases
- Machine learning techniques and algorithms
- Experience with Big data and its tools
The non-technical skills include:
- Exceptional curiosity
- Business acumen and domain knowledge
- Excellent communication skills
Step-3 Read the best books for Data Science
Some great books that Catherine recommends are
- Introducing Data Science, by Arno Meysman and Davy Cielen
- Data science for Business by Tom Fawcett
- Doing Data science by Cathy O’Neil and Rachel Schutt
Step-4 Go for Data Science certifications
- Principal Data Scientist – DASCA
- SAS certified data scientist
- Cloudera Certified Professional (ICCP) Data Science Certificate
- IBM Data Science Professional Certificate
- EMC Proven Professional Data Scientist
- Microsoft Professional Program certificate in Data Scientist
Step-5 Apply for jobs
While applying for jobs for data science, consider the responsibilities of a data scientist and also see what are the applications of data science.
- Perform exploratory data science
- Process, cleanse, and verify the integrity of data
- Identify trends in data and make predictions
- Generate insights using ML techniques
The potential of data science is huge, and the scope of application is increasing swiftly. Here are a few applications trending already.
- Recommendation engines
- Automating risk management
- Real-time and predictive analytics
- Personalised marketing
- Clickstream analysis
- Customer behaviour analytics
A career in data science is all about numbers and your ability to think in the right direction. Data scientists process, model, analyze, and draw conclusions from data to answer complex questions. Hope the aspiring and enthusiastic young people show interest in the field and give a direction to their career. There are many courses, tutorials, and trainings available out there. All it needs is you to recognise your interest and set rolling.
Source: indiaai.gov.in
