Supercharge 

your career with

Long Term Mentorship

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

Move Over traditional courses

Start Making Progress

with 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

600+ mentors are just a Free Trial Session away!

Choose your ideal mentor and get started with a FREE trial session

View All Mentors ->

No need to Struggle Alone Anymore

Long term mentorship gets fully covered

1:1 Live Session

Boost your progress with frequent 1:1 sessions.

Unlimited Chat with Mentor

Get the right advice from your mentor via Chat.

Task & Curated Resources

You will be certified for this mentorship program.

Regular Followups

Stay motivated with regular follow-ups.

Job Referrals

Get referrals to companies by mentor community.

Certified

You will be certified for this mentorship program.

Get Mentored By The Star Mentors

Connect with our star mentors, distinguished leaders in their fields, to receive personalized mentorship.

View All Mentors ->

Ask Mentor Anything

Get answers from our mentors in the forum. They're here to help with your questions about your career.

Ask your questions here

Directly submit your questions to Mentors...

Ask a question ->

Poornima Umapathy | Working Professional

How should I prepare for a Software Development Engineer interview at Amazon?

To prepare for a Software Development Engineer interview at Amazon, you should focus on mastering data structures and algorithms, as well as object-oriented programming concepts. You should also be familiar with Amazon's leadership principles, as they are an important part of the interview process. Additionally, practicing coding problems and whiteboarding exercises can be helpful. Amazon also offers a practice interview tool called Amazon Interview Simulator, which can give you a sense of what to expect in the interview.

Niyati Kapoor | Working Professional

I'm preparing for a business analyst role. How should I go about it?

I have worked with business analyst in my current experience. Skills that business analyst should must have or is having is: 1. They are very at SQL. 2. They are good at handling Excel sheets. 3. They have very good Communication skills . 4. As they have to some time directly talk to customer they should have good language fluent. 5. They are very good at taking and analysing data, for ex. Current growth of users due to some feature release.

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.

Love & Praise by The Mentees

Get inspired by the real-life experiences of our mentee and their journey to success with Preplaced.

Frequently Asked Questions

Find answers to commonly asked questions about Long Term Mentorship