Non-Engg Graduate Lands Dream Job at Google

To start the Google Free Digital Marketing Course, you can:

1. Go to the digital online platform
2. Click Start Course
3. Sign in with Google if you already have one
4. Select Enroll for Free

The course is self-paced and consists of 26 modules. It covers topics such as social media marketing, content marketing, and search engine optimization (SEO). You can download the digital certificate in PDF format after completing the course. 

Google Digital Garage is an online learning platform that offers free digital marketing courses. It has more than 40 courses covering topics like web development, data and analytics, social media, and online marketing. The platform also offers practical exercises and comprehensive modules to help improve your skills and understanding.

Congratulations on completing a Data Science course! Pursuing a career at Google is an exciting goal. To increase your chances of landing a job at Google, follow these steps:

1. Resume and Online Presence: Update your resume to highlight your Data Science course, skills, and any relevant projects or experiences. Ensure your LinkedIn profile is complete and showcases your skills and achievements.

2. Research: Thoroughly research Google, its culture, values, and the specific role you are interested in. Understand the skills and qualifications they look for in candidates.

3. Job Search: Visit Google's official careers website (careers.google.com) to search and apply for suitable Data Science roles. Use keywords like "Data Science, " "Data Analyst, " or "Machine Learning" to find relevant openings.

4. Application: Follow the application process outlined in the job posting. This often involves submitting your resume, cover letter, and sometimes additional materials like a portfolio or work samples.

5. Tailor Your Application: Customize your resume and cover letter for each application, highlighting the skills and experiences that align with the specific role and Google's requirements.

6. Showcase Projects: Highlight any Data Science projects you completed during your course, emphasizing the skills and technologies you used. If you have real-world experience or personal projects, include those as well.

7. Google Cloud and Tools: Familiarize yourself with Google Cloud Platform (GCP) and tools like Google Colab, BigQuery, and TensorFlow. Proficiency in these tools can demonstrate your practical knowledge.

8. Networking: Connect with current and former Google employees on LinkedIn. Attend networking events, conferences, or workshops related to Data Science to expand your professional network.

9. Online Courses and Certifications: Google offers various online courses and certifications (Google Cloud Certifications, TensorFlow Certifications) that can boost your resume and demonstrate your commitment to learning relevant skills.

10. Prepare for Interviews: If you get an interview call, prepare thoroughly. Research common interview questions for Data Science roles and practice your responses. Be ready to discuss your course, projects, and experiences.

11. Behavioral Interviews: Google often conducts behavioral interviews to assess your fit with their culture. Prepare examples of how you've demonstrated key qualities like collaboration, problem-solving, and leadership.

12. Coding and Technical Interviews: Depending on the role, you might have coding or technical interviews. Practice coding exercises and review Data Science concepts related to the role.

13. Problem-Solving: Google values creative problem-solving. Practice solving hypothetical or real-world Data Science problems to demonstrate your analytical skills.

14. Stay Persistent: The hiring process at Google can be competitive and may involve multiple rounds of interviews. Stay persistent, keep applying to suitable roles, and continue improving your skills.

Remember that landing a job at Google can be competitive, so keep honing your skills, learning, and gaining relevant experience to increase your chances of success. Good luck on your journey to joining Google!

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