coursera: Does a data scientist need to know storytelling? More answers can be found in Coursera’s recent career report on skills.
We all want to be part of changing career goals. However, we miss to include some handy key points.
Finding a skills-based approach to jobs and adopting a multidisciplinary approach to developing these skills is the need of the hour. It’s time to skillfully time the clock.
What skills are needed for high-demand jobs?
Data scientist and data analyst professions:
With each business collecting more data than ever before, the need for data scientists and data analysts is only expected to increase. The data scientist’s key job is to find the right insights from the data that can lead to better decisions.
The report found that data management skills are already strong among students who enroll in these courses. But, there are additional skills that students can master for better results. They can try to improve their data visualization skills to present information well and work on telling a data story, in addition to reinforcing fundamental math, probability, and statistics.
Likewise, for data analysts, high-demand tools such as Python and Tableau on Coursera have proven useful for Coursera students.
New Era Engineering Skills:
For a software engineer looking to improve their skills, it is necessary to focus on practical coding, understand data pipelines, learn about systems engineering, data structures and operating systems in more to master programming languages.
Meanwhile, for machine learning engineering, it is necessary to learn computer and statistical programming in addition to mastering machine learning, probability, and statistics.
Marketing is a rapidly changing discipline. Good marketing always relies on good storytelling. But the art and science of marketing has evolved now. While performance marketing and SEO and google adwords should be managed on one side, story and brand building should be done on the other. Marketers, Coursera reports, are therefore now focusing on building communication and data analysis skills. Modern marketing relies on stories and data-driven personalization.
Learning by doing:
To develop in-demand technical skills, learning alone is not enough. Practice, and that too, practice on real-world problems becomes an important ingredient in mastering a skill. Looking at data from their Guided Projects in India, Coursera reported that the following Guided Projects were the best:
- Introduction to game development with Scratch
- AWS S3 Basics
- Create a complete website with WordPress
- Google Ads for beginners
- Get started with Azure DevOps maps
- Create a resume and cover letter with google docs
- Machine learning pipelines with Azure ML Studio
- Developing a business website with WIX
- Get started with Google Analytics
- Business analysis and process management
For young professionals, their skills and competencies can arm them with better exposure to clear jobs.
While India is expected to have one of the best young working-age professionals in the world, in the next few years, this interconnection between skills and practical projects could help more people thrive in employment.
From individual skills to multidisciplinary skills:
Another key insight from the report relates to multidisciplinary pathways. These become increasingly critical when considering the links between skills and careers.
Needless to say, technology skills such as computer programming and statistics are sought after by students of all disciplines.
Additionally, engineering students seek to develop other skills. Math and science students try to focus on leadership skills and communication skills.
Those working to become teachers prioritize research, writing, and communication skills. Arts and humanities students also learn digital skills such as computer graphics, user experience, etc. These can help them enrich and advance their career options such as teaching while gaining a better understanding of human behavior.
Biological science students focus on data analysis, much like business students. The goal is to help them extract patterns from large-scale data. Health science students seek positions in data science.
While the power of deep expertise in a particular area is often seen as essential to success, given the complexity of jobs, multiple skills are needed to solve problems. Polymaths could rejoice.
A skills taxonomy is a means by which these different skills can be mapped for a job.
Our key learning is a taxonomy of skills. Not just for a job, but for investing in a personal skills taxonomy that can help each of us develop interconnected skills throughout our careers. This will further help us map new and uncharted territory with better questions, if not immediate answers.
Today, facets are emerging in the course of each profession. A skills roadmap could guide us on this journey.