Learn what data science careers are emerging and growing popular. Jungwoo also explains steps you can take to make your data science dream job come true.
- [Voiceover] There's no doubt that data science careers are trending upwards. In fact, many industry watchers are reporting shortages in qualified professionals for the foreseeable future. Therefore, I'm happy to say that the outlook for data science job opportunities is extremely bright. Now, the challenge is to prepare yourself for these wonderful opportunities. A good start point is to develop passion for data science by first getting exposed to the field as much as you can.
Once you know you're ready for the task of diving into your journey of training and educating yourself on data science, the next big step to take is to actually commit yourself to lifelong learning. Identify a degree program or online curriculum that will provide a roadmap to your ultimate goal of becoming a data scientist, and simply plunge into it. If you need more guidance, find a mentor who could coach you along the way.
This could be your professor, colleague, or someone you get to know through a LinkedIn invitation. All the careers in data science are fairly new still emerging and evolving. These careers include job titles such as Data scientist, Business intelligence architect, Machine learning specialist, Business analytics specialist, Data visualization developers.
Jungwoo Ryoo is a professor of information science and technology at Penn State. Here he reviews the history of data science and analytics, explores which markets are using big data the most, and reveals the five main skills areas: data mining, machine learning, natural language processing (NLP), statistics, and visualization. This leads to a discussion of the five biggest career opportunities, the four leading industry-recognized certifications available, and the most exciting emerging technologies. Along the way, Jungwoo discusses the importance of ethics and professional development, and provides pointers to online resources for learning more.
- A history of data science
- Why analytics is important
- How data science is used in social media, climate research, and more
- Data science skills
- Data science certifications
- The future of big data