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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

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

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Certified

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rishabh batra | Working Professional

Applied 100+ , but resume didn't get shortlisted, What's the problem here?

Hi Rishabh, If your resume is not getting shortlisted, the problem could be lack of impactful information along with not so good presentation skill. Please reach out to me in case you need help to create an impactful and ATS friendly resume.

Bhavya Kalra | Working Professional

What is the in demand skill to know these days in IT industry?

The IT industry is constantly evolving, and the demand for specific skills can vary depending on the current trends and technologies. However, several skills are consistently in high demand across the IT industry. Here are some of the in-demand skills in the IT industry today: 1. Cloud Computing: Proficiency in cloud computing platforms like Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP) is highly sought after. Companies are increasingly adopting cloud-based infrastructure, and professionals with expertise in cloud services, migration, and management are in high demand. 2. Artificial Intelligence (AI) and Machine Learning (ML): AI and ML technologies are being applied across various industries. Skills in developing AI/ML models, natural language processing (NLP), deep learning, and neural networks are valuable. Understanding frameworks like TensorFlow and PyTorch is also beneficial. 3. Cybersecurity: With the rise in cyber threats and data breaches, cybersecurity skills are in high demand. Knowledge of network security, vulnerability assessment, penetration testing, security operations, and incident response is valuable. Certifications such as Certified Information Systems Security Professional (CISSP) or Certified Ethical Hacker (CEH) can enhance your credentials. 4. Data Science and Analytics: Proficiency in data analysis, data visualization, statistical modeling, and data mining is increasingly important. Skills in programming languages like Python and R, as well as data manipulation and analysis tools like SQL and Apache Spark, are highly desirable. 5. DevOps: The DevOps approach emphasizes collaboration between software development and operations teams to streamline software delivery and infrastructure management. Knowledge of DevOps tools like Docker, Kubernetes, Jenkins, and Ansible, along with skills in continuous integration and continuous deployment (CI/CD), is in demand. 6. Full-stack Development: Full-stack developers who have expertise in both front-end and back-end development are highly sought after. Proficiency in popular web technologies, such as HTML/CSS, JavaScript, and frameworks like React or Angular for the front end, combined with skills in server-side programming (e.g., Python, Java, Node.js) and databases (e.g., SQL, NoSQL), is valuable. 7. Internet of Things (IoT): IoT is expanding rapidly, and professionals with skills in IoT architecture, sensor integration, data management, and security are in demand. Knowledge of IoT platforms, protocols, and cloud integration is beneficial. 8. Agile and Scrum: Agile methodologies, such as Scrum, are widely adopted in software development projects. Familiarity with Agile principles, iterative development, and Scrum frameworks is valuable. Agile certifications, such as Certified ScrumMaster (CSM), can be advantageous. Remember that the IT industry is diverse, and specific skills may vary based on the organization, industry sector, and geographical location. Stay updated with the latest trends, continuously learn and adapt to emerging technologies, and showcase your expertise in areas aligned with your career goals and interests.

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.

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