Data science and artificial intelligence are exciting, growing fields with a lot to offer prospective job seekers. However, even with the massive growth in technology and positions, there are still many barriers to entry. This course explores today’s challenges and opportunities within data science and artificial intelligence, the varying skills and education necessary for some commonly confused positions, as well as the specific job duties associated with various in-demand roles. By taking this course, learners will be able to discover which role and industry best fit their skills, interests, and background as well as identify any additional education needed, both of which will prepare them to apply and interview for DS/AI positions.
Identifying the Right Role for Yourself
This course is part of Interviewing for DS/AI Roles Specialization
Instructor: Camille Funk
Included with
Recommended experience
What you'll learn
Identify the required skills, education, and experience for various DS/AI roles.
Describe a DS/AI role that aligns with personal goals and area of interest.
Assess what additional skill training is needed to enter a specific DS/AI role.
Skills you'll gain
Details to know
Add to your LinkedIn profile
4 assignments
See how employees at top companies are mastering in-demand skills
Build your subject-matter expertise
- Learn new concepts from industry experts
- Gain a foundational understanding of a subject or tool
- Develop job-relevant skills with hands-on projects
- Earn a shareable career certificate
Earn a career certificate
Add this credential to your LinkedIn profile, resume, or CV
Share it on social media and in your performance review
There are 4 modules in this course
Welcome to Module 1, Data Science and Artificial Intelligence Field & Roles. Now that you’ve finished school or accumulated some initial experience in the data science and/or artificial intelligence fields, you’d probably like to find a full-time, long-term position. In this module, we’ll discuss the current DS/AI landscape, some of the common challenges of landing a DS/AI role, and the basic experience and education you will need to be considered for a DS/AI role. We’ll close the module with a discussion about your current DS/AI experience, education, and goals for the future. We’ll use this as a benchmark to reflect on at the end of the course and specialization.
What's included
2 readings1 assignment1 discussion prompt2 plugins
Welcome to Module 2, Data Scientist vs Data Analysts vs Data Engineer. Data scientists, data analysts, and data engineers are roles we’ve all heard about in passing but what do they really entail? In this module, we will explore the responsibilities and required skills for these roles, along with identifying the similarities and differences between the three. We will also discuss if any of these positions align with our personal interests, skills, personalities, and future goals.
What's included
2 readings1 assignment1 discussion prompt1 plugin
Welcome to Module 3, Machine Learning and AI Jobs. Now that we’ve explored some data science roles, let’s transition over to a few specific ML and AI roles. In this module, we’ll review some common ML/AI roles, identify the skills necessary for securing and advancing in one of these roles, and discuss how data science and artificial intelligence roles overlap and how they differ.
What's included
2 readings1 assignment1 discussion prompt1 plugin
Welcome to Module 4, Other Data Science Positions. We will wrap up this course by reviewing a few more DS/AI roles that are currently in demand. Like the roles mentioned in other modules, there can be some confusion around what exactly the data architect, cloud engineer, and business analyst roles involve. In this module, we will examine the different responsibilities and required skills and experience for each of these roles. We will also determine which DS/AI role and industry best align with our personal goals, skills, and interests.
What's included
2 readings1 assignment1 discussion prompt2 plugins
Instructor
Offered by
Recommended if you're interested in Data Analysis
University of Pennsylvania
University of London
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