Frequently Asked Questions
Is This Course Right for Me?
If you’re looking to build a career in data science or switch careers, this is a great course to start.
The course is suitable for those who are entering into the work force fresh from college as well as young professionals with 2-3 years of work experience and seeking a data science career.
Yes, the course is available to international students as well.
Yes, the course is designed in such a way that individuals from non-coding and non-technical backgrounds having basic appreciation of mathematics and statistics can pick up.
Yes, the course is designed for self-paced individual lead learning. You can plan your time and pace for learning.
No, the course is ideal for both recent graduates and experienced professionals.
While some institutes may offer the option to audit part of the course before enrolling, this course by Bhrighu is not open to audit.
The course is backed by industry-recognized certification. Undergoing this course will provide you with the tools, skills and knowledge required to shift into data science.
Yes, since the course is flexible and self-paced, you can easily manage both your job and studies.
If you successfully complete this course and clear the proctored exam you will be automatically listed in NASSCOM’s Job portal highlighting your skills and competencies. Companies wishing to hire and visiting NASSCOM portal will have visibility to your profile.
Pre-requisites
No, there are no specific prerequisites. If you want to really master then some amount of coding knowledge would be beneficial.
No, Python will be taught from scratch.
Basic knowledge of math is helpful, but the course covers necessary math concepts like Linear Algebra, Statistical Modeling in detail.
No, a degree in computer science is not necessary for enrolling in the course. If you are from computer science background a few topics may be very easy to pick up.
No. The course is designed to teach programming from the ground up, particularly Python. If you have programming experience you will be able to complete the course faster.
Basic understanding of statistics, linear algebra, and probability is useful but will be covered in the course.
No, the course will start from introductory machine learning concepts.
No, this course is open to both fresh graduates and professionals without prior data science experience.
Topics Covered
Topics are divided into foundational topics like Linear Algebra, Statistics, R, Python programming, machine learning, and Tensor Flow. You also have the option to choose one advanced topic as an Elective. You will get to make this choice after you have paid the fees and are enrolled in the course.
Yes, data cleaning and preprocessing are core components of the curriculum.
You’ll work with datasets from various industries like finance, healthcare, and e-commerce.
Yes, machine learning model building is a key part of the curriculum.
Python is the primary language taught in the course.
While the course is titled Data Science Essentials, we will provide you with an option to choose from a list of advanced topics in Data Science.
Yes, data visualization is a major topic covered in the course.
Yes, the course includes real-world applications of data science concepts through hands-on projects.
Basic big data concepts will not be covered in this course.
Yes, data ethics and privacy are minor parts of the curriculum.
Pedagogy
The course uses a hybrid pedagogy which is mix of recorded content, live virtual sessions and practical assignments.
It includes live sessions, recorded lectures, quizzes, and assignments.
The course is self-paced. Live sessions with faculty and SME are scheduled from time to time. Notifications on live sessions will be sent to each learner through notifications and emails.
One needs to invest around 2 hours per day. Around 10-12 hours per week is recommended.
Yes, you’ll have access to all course materials up to 6 months after completion of the course. This will ensure that you are well prepared when you appear for job interviews.
Yes, some course materials can be downloaded for offline access.
Yes, the course is delivered in English.
The course is self-paced, but it is recommended to complete it within 6 months.
Live sessions are conducted weekly via online platforms where participants can interact with instructors.
Yes, the course is designed to accommodate part-time learners as well.
Doubt Clearing Sessions
Participants receive support through live interactions, doubt-clearing sessions, and a dedicated student success team that will respond to their queries on email within 48 hours.
Doubt clearing sessions are moderated by Instructors from Bhrighu who are subject matter experts and industry veterans. You can ask questions directly during live sessions.
Doubt-clearing is usually done during live group sessions.
All live sessions are recorded and available for review later.
Yes, the system architecture is designed to provide feedback on quizzes and assignments. Comprehensive feedback by Instructors and SME is provided to live projects.
We have a dedicated email id. Your queries will be relayed to instructors via forums or email and they will respond directly to you.
Project mentors are not provided as part of this course. We strongly encourage students to identify mentors / coaches who are able to give them time in their development.
Yes, study groups and online forums are often part of the course to foster peer learning.
Group projects may be included depending on the course design.
Yes, the student success team assists with any doubts or challenges during the course.
Assessments and Grading
Through quizzes, assignments and project work.
Yes, quizzes and assignments are graded to assess your understanding of the course materials. The course Director has given different weightages based on topics and their importance in mastering data science.
Yes, assessments are included at regular intervals throughout the course to evaluate your progress.
Yes, Bhrighu allows retaking quiz and resubmission of assignments where required.
Yes, there is a final exam. This final exam is proctored by NASSCOM FSP, ensuring the integrity of the certification process.
Projects are graded based on your implementation of data science concepts and the quality of your analysis.
Yes, upon successful completion, you will receive a certificate from Bhrighu. If you successfully clear the proctored exam you will also receive NASSCOM FSP certificate.
Some courses include module-based exams or assessments to ensure progress.
Yes, successful completion of all quizzes, assignments, and projects is usually required to earn the course completion certificate.
Assessments typically take one to two weeks to grade.
Project Work
Projects include data analysis, machine learning model building, and a capstone project to simulate industry scenarios.
Group projects may be included and offered for some topics. The course Director takes a decision on this
You’ll build a portfolio with live projects, which you may want to share with potential employers to showcase your competencies and skills.
The capstone project is the final project where you apply all the learned concepts to solve a real-world problem.
Mastering Individual topics themselves is one thing. Being able to connect the learning to business issues requires a different level of thinking. Capstone projects are meant to develop this competency
You will use tools like Python, Jupyter Notebooks, and data visualization libraries during the project work.
Bhrighu is open to student learning bringing their own project from their work place. The decision to work with your own project requires an approval from the Course Director. Individual learners have to seek this approval on email
Yes, instructors will provide detailed feedback on your capstone project.
Selected capstone projects are put up for industry expert review.
Yes, your capstone project is a key part of your portfolio to showcase to potential employers.
Tools
Tools include Python, Pandas, Matplotlib, and Jupyter Notebooks.
Python is the primary language taught in the course.
No additional purchases are necessary. The course provides all materials and uses free tools.
Primarily Python, along with libraries like Pandas, Matplotlib, and Scikit-learn.
Yes, all the tools you will use in this course, like Python, Pandas, and Jupyter Notebooks, are open-source.
Basic cloud tools may be introduced depending on the course structure. Licensed cloud based tools may not be integrated in this course.
A standard laptop or desktop is sufficient for this course.
Yes, all tools and libraries used in the course are compatible with standard computers.
Yes, you’ll need to install Python and relevant libraries like Pandas and Matplotlib, which are free.
Yes, Jupyter Notebooks is one of the primary environments you’ll use during the course.
Why should I choose this course over others?
The content has been vetted by EY and rated Excellent for applicability at work place. This course offers a NASSCOM-accredited certificate, real-world projects, and personalized instructor support.
You’ll gain proficiency in data science fundamentals, machine learning, and data analysis techniques.
NASSCOM-accredited certification, Industry-vetted curriculum, 50% discount on market price, Money-back guarantee as part of GOI incentive scheme
It consists of recorded lectures, live interactive sessions, quizzes, assignments, and a capstone project all designed to give you real-world experience in data science.
The course is aligned with NASSCOM FSP standards, ensuring that it meets the latest industry requirements for data science roles.
You’ll work on real-world projects aligned with current industry trends.
Yes, the NASSCOM-accredited certification increases your employability in the data science industry.
Yes, all instructors have real-world experience in data science.
Yes, the curriculum is updated to reflect the latest developments in data science.
Proctored Exam and FSP Certification
Yes, the course is NASSCOM-accredited and industry-recognized.
Yes, upon successful completion of the course you will receive vouchers for appearing in a proctored exam. If you clear that exam, you will receive a NASSCOM-accredited certificate.
Yes, the final exam is proctored, ensuring the integrity of the certification process.
Yes, the certification is NASSCOM-accredited and vetted by industry leaders such as EY.
The certification signals your readiness for data science roles to employers.
The certification does not expire and remains valid throughout your career.
Yes, the course typically ends with a proctored final exam that must be passed to earn the certificate.