Data Science Course

Most courses accept graduates from any discipline. Having a background in computer science, statistics, or engineering helps, but it is not mandatory. Basic knowledge of mathematics and logical reasoning is useful to keep up with the pace of the program. 

Yes. Many beginner-friendly courses start with teaching Python and SQL from scratch. While coding is essential in data science, you don’t need prior knowledge to enroll. With structured guidance, even non-programmers can build proficiency. 

Yes. Since most coursework involves coding, data analysis, and visualization tools, a laptop with at least 8GB RAM and stable internet is recommended. Higher specifications are useful if you plan to work with deep learning models. 

Yes. Non-technical graduates can enroll if they are willing to learn programming and statistics. Many successful data scientists come from fields like economics, biology, and management after taking structured courses. 

Yes. Most DS courses for beginners emphasize basics such as statistics, Excel, and Python, which makes them suitable for freshers and non-technical backgrounds. A beginner-friendly data analytics course also follows a similar approach.

First, identify whether you want to become a data analyst, data engineer, or data scientist. Then choose the best DS course or data analytics course that suits your aspirations, budget, and learning speed.

upGrad provides hands-on training, mentorship, and career assistance-supported by IIIT Bangalore and international partners such as LJMU, making it among the top DS course in India.

Yes. A DS course with projects enables you to take up positions such as Data Analyst, Data Scientist, and Machine Learning Engineer.

Major recruiters are Microsoft, Google, PwC, JPMorgan, and Tiger Analytics. They prefer experiential project work and certifications from established institutions.

Anticipate projects on retail analytics, fraud detection, customer segmentation, and developing ML models, all working with industry use-cases across industries like e-commerce and banking.

All of upGrad's mid- to long-term DS courses have 16+ real-world industry projects, such as NLP, ETL pipelines, and dashboarding assignments. These are designed to make you placement-ready and provide practical exposure, particularly if you're taking a data scientist course with placement and career assistance.

This project entails working with movie and IPL data by applying tools of data manipulation, slicing, visualization, and dashboarding. It's particularly helpful in a data analytics course that emphasizes data storytelling, data analysis, and business intelligence.

You will gain hands-on skills in cloud computing (AWS), data warehousing, and real-time data transformation, all of which are in great demand in data engineering and DS job positions.

A DS course takes anywhere from 3 to 24 months to finish. Short-term (3-6 months) certification courses are perfect for upskilling in a snap, while long-term (12-24 months) master's levels provide in-depth specialization and international credentials.

Professional working individuals can opt for flexible online courses such as the Executive Post Graduate Program from IIIT Bangalore (12 months) or MS in Data Science from LJMU (17 months). They provide part-time education, hands-on projects, and established data science certifications.

Yes, particularly for newcomers or rapid upskilling. upGrad has short-duration programs such as the Microsoft Generative AI Mastery Certificate and PwC Academy's Business Analytics & Consulting Program (3 months), both specialize in core technologies such as Python, SQL, and data visualization.