Find the latest and informative post on Data Science. Keep yourself updated, know the current trends in Data Science industry and use cases for data viz and data storytelling.
In this article, we’ll address the Data Science vs. Data Analytics debate, focusing on the difference between the Data Analyst and Data Scientist.
Want to learn why data science is important and how it works? Know about the 8 ways data science brings value to the business and increases growth exponentially.
This article walks you through all the phases of the data science life cycle and helps you ace your data science career.
The only prerequisite for the course includes a little experience in programming and hold in Engineering mathematics (such as calculus, probability, differential equations, Linear Algebra, etc.).
Bachelor’s Degree with minimum 50% or equivalent passing marks. No coding experience is required.
Like any other scientist, a data scientist has a fair few tools in her arsenal, which they use based on the situation. For example, suppose the problem is obvious enough. In that case, it can be solved using a simple visualization, which will be made in a BI tool like tableau or even MS Excel to some extent; as the problem becomes more complex, the tools to be used to crack them become more sophisticated. They might range from the plain vanilla logistic regression to an ensemble of neural networks built to utilize data coming from an NLP functioning.
Data Science is one of the most popular career choices with tremendous opportunities and high demand. Every industry is now leveraging data to help them build strategies and plan for the future. With Data Science, you can solve real-life challenges and provide smart solutions to many, which is why Data Scientist has been called "the most promising career" by LinkedIn and the "best job in America" by Glassdoor.
Yes, Statistical analysis helps to generate statistics from stored data. The results can then be analyzed to infer insights and conclude meaning about the entity being analyzed.
This program is well suited for freshers or experienced professionals.
You’ll be using programming languages to organize, clean, and make sense of data. Hence, you need to be fluent in its use to perform these basic tasks efficiently. Work and develop mastery in R, Python, Perl, Java, C/ C++, and SQL. Python and R are the most important programming languages for coding in data science.
The top skills you will learn are Predictive Analytics using Python, Machine Learning, Data Visualization, Big Data, Natural Language Processing.
Common Curriculum: Basics of SQL, Python, Statistics, and EDA, Basic Machine Learning Models
Data Science Generalist: Advanced Machine learning & Storytelling, Advanced Programming & Databases
Deep Learning Specialization: Advanced Machine Learning, Neural Networks
NLP Specialization: Advanced Machine Learning, Natural Language Processing
Business Intelligence: Advanced SQL and NoSQL Databases, Storytelling with Advanced Visualization
Business Analytics: Advanced Machine Learning, Storytelling, and Advanced Business Problem Solving
Data Engineering: Data Modelling and Data Warehousing, Building Data Pipelines, Data Streaming, and Processing
It varies with the program/course you choose. For Executive PG Programme in Data Science in collaboration with IIITB, duration is 12 months with recommended 12-15 hrs/week. You can refer to our website pages for complete information offered and the brochures.
Analysts predict that the country will have more than 11 million job openings by 2026. In fact, since 2019, hiring in the data science industry has increased by 46%. Yet, around 93,000 jobs in Data Science were vacant at the end of August 2020 in India. Data Science and Machine Learning have a steep learning curve.