Specialists in machine learning (ML) and artificial intelligence (AI) are at the forefront of reshaping our perceptions of the workforce.
As per the World Economic Forum’s 2023 Future of Jobs Report, the industry is poised to grow by 40% in the next five years, generating one million new job opportunities, marking the most substantial surge across all professions.
Moreover, acquiring expertise in these sought-after domains can yield significant returns on investment, despite the fact that many AI and ML applications are still in their infancy. Companies like Papa John’s and Canva are allocating substantial resources to AI implementation, underscoring the importance for employees to possess essential skills such as Python programming, agile engineering, and natural language processing.
Fortunately, there are numerous avenues available for individuals to develop these competencies. Online platforms like Udemy offer a plethora of courses catering to various skill levels, sizes, and price points. Furthermore, individuals can pursue paid courses and certification programs from reputable universities and tech companies from the comfort of their homes.
For those seeking a structured learning experience, enrolling in a program system could be a viable option. These programs often provide more comprehensive insights compared to individual courses or shorter certificates, while being more time-efficient, cost-effective, and adaptable than traditional degree programs. Some programs also offer workshops that are instrumental in providing mentorship and career services, assisting students through every stage of the job search process, from networking to salary negotiations.
Springboard’s machine learning and AI program, launched earlier this year in collaboration with three universities, exemplifies the growing emphasis on training in this rapidly evolving field.
Kara Sasse, the Chief Product Officer at Springboard, highlights that the bootcamps are tailored to meet the needs of working professionals aiming to progress in AI-centric work environments. She emphasizes the importance for forward-thinking companies to identify and address potential skill gaps by recruiting professionals equipped with the requisite expertise to thrive in the evolving landscape shaped by ML and AI technologies.
Springboard’s programs are designed to enhance students’ technical skills in areas like data processing and system architecture through hands-on projects and practical exercises, in addition to fostering soft skills such as problem-solving and strategic thinking.
Nelis Parts, CEO of Fullstack Academy, mentions that their AI and ML program covers foundational concepts and emphasizes practical applications, culminating in a career-simulated project at the end of the six-month program.
Parts underscores the significance of facilitating individuals from diverse professional backgrounds to access in-demand AI and ML knowledge, thereby bridging the tech skills gap, especially with companies gearing up to invest significantly in AI in 2024 alone.
He notes, “The rapid adoption of AI and machine learning technologies has brought about profound transformations across various industries. Consequently, roles in AI and machine learning architecture are now highly lucrative and sought after.”
Both Springboard and Fullstack Academy take pride in the successful placements of their program alumni in companies of all sizes and sectors, including tech giants like Amazon and Google.
However, these initiatives are just a glimpse of the myriad opportunities available in the ML and AI domains. Several program options are listed below, with durations typically ranging from eight to nine months and costs varying from a few thousand dollars to nearly $15,000.
Partners: University of Central Florida, UNC Charlotte, University of Denver, University of Kansas, University of New Hampshire, University of Richmond, University of Utah, Arizona State University, Columbia University, Michigan State University, and Ohio State University.
Price: $3,499
Duration: 8 to 10 days
Prerequisites: Job experience recommended, proficiency in Python and mathematics including linear algebra, statistics, and calculus.
Topics covered: machine learning in marketing, neural networks, deep learning, and natural language processing.
N/A Partners
Price: $14,495
Duration: 6 months
Prerequisites: Coding experience preferred, background in post-secondary math, and/or three to five years of work in a computing-related field.
Topics covered: Applied Data Science with Python, Deep Learning, Generative AI, and Prompt Engineering.
Partners: Caltech and UT-Dale
Cost: \(10,000 (Caltech) and \)8,000 (UT-Damas)
Duration: 6 months
Prerequisites: Programming and math proficiency, ideally two years of formal work experience.
Topics covered: ChatGPT, Prompt Engineering, Applied Data Science with Python, Keras and TensorFlow for Deep Learning, and Essentials of Generative AI.
Partners: University Global, University of Maryland Global Campus, and UC San Diego Extended Studies
Price: $13,950
Duration: 9 months (15 to 20 hours per week)
Prerequisite: Proficiency in Python, Java, or JavaScript.
Topics covered: Machine Learning Models, Deep Learning, Ethics, and Bias in Machine Learning.
