New Skills, New Confidence, and a New Data Science Career
A few years after finishing graduate school, I decided I wanted to make a career transition into data science. I had some experience with related concepts from the work I’d done for my PhD, but I needed to fill in a number of gaps in my background knowledge and skills. I also needed a flexible learning environment, so I could continue working while I gradually adjusted my career path.
Coursera was a great way to build the skills I needed. Courses like Machine Learning (Stanford) and Data Science at Scale (University of Washington) helped me connect concepts, build on my previous coursework, and gain experience working through programming and machine learning examples using real datasets.
But finding a job in data science wasn’t easy – it took persistence, and it was easy to get discouraged. As I started looking for jobs and interviewing, Coursera helped me push through the frustrations and disappointments. The courses I took gave me a professional, technical vocabulary to use in interviews, and confidence that I could contribute to a data science team.
Today, my work has paid off. I’m a Senior Associate Analytical Consultant at a major statistical software company, using neural networks to improve fraud detection systems. The courses I took on Coursera are directly applicable to my new job, and my hands-on project experience allowed me to quickly adapt to my new team and contribute to projects. I feel that Coursera has empowered me to be a lifelong learner, and I’m continuing to take courses to keep my skills relevant.