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Long Term Mentorship

1-on-1 long-term mentorship with your chosen mentor to guide you to the career you deserve

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1:1 Long Term Mentorship

30%

Cheaper

Compared to any 6 month course

4x

Results

As compared to any online courses

50%

Faster

Get a results within 6 months instead of years

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1:1 Live Session

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Unlimited Chat with Mentor

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Task & Curated Resources

You will be certified for this mentorship program.

Regular Followups

Stay motivated with regular follow-ups.

Job Referrals

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Certified

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Niyati Kapoor | Working Professional

How can I switch from SDE to Data Science role?

Switching from a Software Development Engineer (SDE) role to a Data Science role requires a combination of acquiring new skills and leveraging your existing technical expertise. Here's a roadmap to help you make the transition: 1. Assess your current skills and knowledge: Evaluate your existing programming skills, especially in languages commonly used in data science like Python or R. Identify the areas where you have a strong foundation, such as algorithms, data structures, and software development practices. These skills will be valuable in your transition. 2. Understand the field of data science: Gain a solid understanding of the key concepts, techniques, and tools used in data science. Familiarize yourself with statistics, machine learning algorithms, data preprocessing, data visualization, and other relevant topics. Online courses, tutorials, and textbooks can be valuable resources for learning. 3. Learn programming languages and libraries: Develop proficiency in Python or R, as these languages are widely used in data science. Familiarize yourself with data science libraries and frameworks like pandas, numpy, scikit-learn, TensorFlow, or PyTorch. Practice coding exercises and work on data science projects to apply your knowledge. 4. Gain knowledge in statistics and mathematics: Data science heavily relies on statistical analysis and mathematical modeling. Strengthen your understanding of statistical concepts such as hypothesis testing, regression analysis, and probability. Brush up on linear algebra and calculus, as they are foundational for certain machine learning algorithms. 5. Take data science courses and certifications: Enroll in online or in-person courses specifically tailored to data science. Platforms like Coursera, edX, and Udacity offer a wide range of courses on statistics, machine learning, data analysis, and data visualization. Completing reputable certifications can also boost your credibility. 6. Work on data projects: Start working on personal data science projects to gain hands-on experience. Seek out datasets from open data sources or Kaggle, and apply your knowledge to analyze and derive insights from the data. These projects will help you build a portfolio and demonstrate your practical skills to potential employers. 7. Network with data scientists: Engage with professionals in the data science field to expand your knowledge and make connections. Attend data science meetups, conferences, and online forums. Networking can provide valuable insights, mentoring opportunities, and potential job leads. 8. Customize your resume and cover letter: Tailor your resume and cover letter to highlight relevant skills, projects, and experiences that align with data science. Emphasize any data-related work or projects you have done during your SDE role. Highlight transferable skills such as problem-solving, analytical thinking, and teamwork. 9. Apply for data science internships or junior positions: Consider applying for internships or entry-level data science positions to gain practical experience. These roles can help you bridge the gap between your SDE background and a full-fledged data science role. Be open to starting at a junior level and gradually progressing as you gain more experience. 10. Prepare for interviews: Familiarize yourself with common data science interview questions and practice answering them. Be ready to discuss your projects, your approach to solving data problems, and how you have used your programming and problem-solving skills in a data-driven context. Leverage your software development experience to showcase your ability to implement solutions efficiently. Remember, transitioning to a data science role may take time and effort. Continuously build your skills, stay updated with industry trends, and be persistent in your job search. With the right combination of technical knowledge and practical experience, you can successfully switch from an SDE role to a data science role.

Sneha Mehra | Working Professional

How to fill up the ‘Experience’ section in resume being a fresher?

You can definitely get short term and long term internships through Linkedin and other platforms. If you are in your 1st/2nd year of college they do not really expect you to have a lot of experience and some good projects can actually make up for it!

Bhavya Kalra | Fresher

How do I build a strong resume?

List down all your competency and build your resume around it, it will help you to invision what is important and what is not. You have to carefully scan the jbo description for the role you are targeting.

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