Meet data scientist, lifelong learner, and AI Community Leader Mo who has completed more than 40 courses on Coursera! Recruiters contacted him and chose him out of 200 other candidates to be a co-founder and Chief Data Scientist at an AI startup after seeing his certificates from the Deep Learning Specialization and TensorFlow in Practice Specialization. In his own words, Mo shares his learning journey with us.

About me

I’m a Data Scientist in Lebanon who’s passionate about artificial intelligence. I currently work at Rebaie Analytics Group to develop algorithms in computer vision, natural language processing, and other deep learning fields. 

In college, I started reading about the impact of data science in transforming business and even in the way humans interact with machines in our daily lives. Further inspired by the AI influencer and keynote speaker Ali Rebaie, I wanted to apply an anthropological perspective to solve current AI challenges.

Like I do with any subject I’m interested in, I jumped right into learning everything I could, starting with taking machine learning courses online. I was glad to find Coursera – it’s really the most effective and interactive e-learning platform out there.  

Building a foundation in data science

I started with a few courses that could help me build a solid foundation:

• Machine Learning from Stanford
• Mathematics for Machine Learning Specialization from Imperial College London
• Deep Learning Specialization from Deeplearning.ai

I believe that learning is a continuous path, especially in the sciences. So even though I have a job right now, I want to keep learning new things to stay up-to-date. That’s why I recently took the IBM Data Science Professional Certificate to enhance my knowledge and expand my skills. 

I liked that the program had introductory courses covering a wide range of topics with practical assignments, engaging and clear video lectures, and easy-to-understand explanations. 

As with the other courses I took on Coursera, this program strengthened my portfolio and helped me in my career.

Growing my career

Recently, a recruiter contacted me about a Chief Data Scientist position at an AI startup! And this is just one of many job opportunities that I’ve discovered. The amazing thing is that they are noticing my certificates from Coursera, especially the Deep Learning Specialization and TensorFlow in Practice Specialization!

Coursera has really changed my life. I’m achieving my dreams and continuously growing in my career. I want to raise awareness for Coursera as a learning destination for all people, especially in my country, because we don’t have data science and AI degrees in Lebanon. One of the only ways for us to really learn about these subjects is through online courses so Coursera is an invaluable resource.

My advice for you

Whether you’re just getting started or well on your way in your data science career, these are some tips that have helped me along my journey and I hope they will help you, too.

• Embrace curiosity and learn new things.
• Online courses are more accessible and available now than ever before. You don’t need a traditional degree to work in the AI or any other tech field. You can get the training and experience you need online!
• Don’t just collect certificates––you also need to really understand what you’re learning and put that into practice. Certificates are there to celebrate your successes.
• Read continuously. Blogs and articles are great for staying up-to-date in the field.
• Leverage social media. Follow and interact with leaders, experts, and influencers in the field you’re interested in. Share your certificates and accomplishments with your network to build a strong portfolio.
• Time management is essential to success––build a schedule and allot time for making progress in your courses.
• Join the Coursera Community to engage with other learners and learn from their experiences.

I’m also always available and there to support you on your journey in AI as well. You can find me on Twitter, LinkedIn, the Coursera Community, the deeplearning.ai community, Github, and Kaggle!

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