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.
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By the end of this course, students will be able to:
• Identify the required skills, education, and experience for various DS/AI roles.
• Recall the similarities and differences between various commonly confused DS/AI roles.
• Describe a data science/artificial intelligence role that aligns with personal goals and area of interest.
• Assess what additional skill training is needed to enter a specific DS/AI role.
Course 1 of 3 in the Interviewing for DS/AI Roles Specialization.
What You Will 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.
Syllabus
WEEK 1
Data Science and Artificial Intelligence Field & Roles
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.
WEEK 2
Data Scientist vs. Data Analysts vs. Data Engineer
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.
WEEK 3
Machine Learning and AI Jobs
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.
WEEK 4
Other Data Science Positions
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.
