Top AI & Machine Learning Careers and Salaries
While demand for data scientists in general is slated to increase over 36% over the next decade—much faster than the 6% average growth rate of all professions—AI & machine learning specialized roles are a huge contributing factor to the expansion of the data science industry (Bureau of Labor Statistics). That means data roles concentrated in artificial intelligence are constantly growing and evolving along with the industry itself.
With these professionals in high demand, the data industry offers a range of opportunities to those who’ve gained working experience as well as specialized knowledge in the field.
Browse the table below to see how these roles compare, then read on to discover the right career path for you.
Role |
Salary* |
Business Analyst |
$70,319 |
Data Analyst |
$71,034 |
Artificial Intelligence Engineer |
$123,392 |
Data Scientist - AI/ML |
$142,418 |
Machine Learning Engineer |
$151,063 |
*US Median Salary Data, May 2023, ZipRecruiter
What You’ll Learn in the Fullstack Academy AI & Machine Learning Bootcamp
The part-time Artificial Intelligence and Machine Learning Bootcamp is divided into 6 units. Starting with Statistics Essentials for Data Science, you’ll quickly move into more advanced computing and engineering concepts—with a career-simulated project at the end of bootcamp to help you practically apply your skills.
- Statistics Essentials for Data Science - Apply the principles of data science in a real-world context–emphasizing ethical practices and effective decision-making.
- Programming Basics - Acquire experience loading, storing, and working with data in Python.
- Applied Data Science with Python - Gain an in-depth understanding of data science processes including data wrangling, data exploration, fundamental and advanced statistics, and hypothesis building and testing.
- Machine Learning - Learn and deploy machine learning principles, algorithms, models, and applications.
- Deep Learning - Explore deep learning and leverage neural networks to create and optimize models using tools.
- Generative AI & Prompt Engineering - Examine generative AI, including ChatGPT and prompt engineering. Learn to effectively and ethically utilize them for a variety of business applications.
Admissions Process
The Fullstack Academy AI & Machine Learning Bootcamp is designed to support students of all skill levels. There’s no experience required to apply or be accepted.
However, we recommend prospective students possess one or more of the following:
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Experience coding in any language
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Formal education/professional use of post-secondary math including Linear Algebra, Calculus, or Statistics
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3-5 years of employment in a highly computational field
Beginners looking to break into the data field are invited to consider the Fullstack Academy Data Analytics Bootcamp, which will provide you with the foundational knowledge and technical skills you'll need to pursue more advanced specializations in the data field as a career.
A Day in the Life of an AI Bootcamp Student
In the part-time Artificial Intelligence and Machine Learning Bootcamp, you’ll experience a mix of live instruction, workshops, and projects to help you develop and hone your skills in 26 weeks online.
All classes are held on Mondays, Wednesdays, and Thursdays each week from 7:30pm - 10:30pm ET.
Demos & Collaborative Exercises
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Through active demonstrations, your instructor will introduce or demonstrate knowledge and skills related to the unit.
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After this, you’ll participate in inquiry-based labs and challenges to reinforce what you’ve learned.
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Our instructional team members will then be available to assist you or your team in solving challenges.
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To conclude class, your instructor reviews the topics covered and ensures student understanding of the homework assignment(s).
Each week, students can expect to spend 9 hours total in class, plus about 20+ hours studying or working on outside assignments.
Class time options are subject to change. To see available class times for your cohort of choice, complete your application or schedule a call with a student advisor.
Career Success
Students will gain valuable insight into how to build a successful career in the data field and AI specializations from day one of the course. Throughout the bootcamp experience, students may access live workshops, office hours, and asynchronous modules to help build a job search toolkit - which includes an optimized resume and LinkedIn profile.
Following successful completion of the Career Success Program, students can choose to opt into additional career coaching support and receive guidance for up to a year following graduation in:
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Growing your professional network
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Resume and LinkedIn profile optimization
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Interview and assessment prep
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Salary negotiation workshops
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And much more!
You’ll also graduate from the program with a portfolio of work that demonstrates your ability to solve real business problems for real companies.
Fullstack Academy Graduates Get Hired
Fullstack Academy grads have landed jobs with some of the world's leading companies.
Some examples of companies hiring Fullstack Academy graduates include:
- Facebook
- Bloomberg
- Google
- Spotify
- Simon
- BlackRock
- Datadog
- Amazon
AI & Machine Learning Bootcamp FAQs
Q: Is the Fullstack Academy AI & Machine Learning Bootcamp for beginners?
A: Yes, the Fullstack Academy AI & Machine Learning Bootcamp is designed to support learners of all levels, including beginners.
However, for optimal success in the bootcamp and beyond, we recommend students possess one or more of the following:
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Experience coding in any language, ideally Python
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Formal education/professional use of post-secondary math including Linear Algebra, Calculus, and Statistics
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3-5 years of employment in a highly computational field
Q: What will I learn in the Fullstack Academy AI & Machine Learning Bootcamp?
A: Please note that the bootcamp is a highly computational, programming-based tech training program that teaches artificial intelligence and the machine learning tools, technologies, and processes that support its development. Students will learn how to create and deploy this technology toward a range of applications.