Learn how to harness the power of artificial intelligence to transform your workflow with hands-on training in ChatGPT and Microsoft Copilot. This course will teach you how to generate content, streamline tasks, and integrate AI into business communication, writing, analysis, and productivity tools.
Harness the creative power of AI with this hands-on workshop. Explore the cutting-edge world of artificial intelligence and learn how to generate text, ideas, and more with the innovative technology of ChatGPT.
Leverage the power of cutting-edge AI tools and features in Photoshop, Illustrator, InDesign, and other Adobe apps in this hands-on class.
Learn how to use generative AI to improve your video and motion projects. Create visual and audio assets, integrate AI tools into your daily workflow, and learn how copyright and data confidentiality work when using AI content.
Learn how to incorporate AI in your marketing strategy with this in-depth course. Explore how to use AI-driven tools to help your SEO, SEM, social media marketing, analytics tracking, paid advertising, and more.
Master AI technologies for business, marketing, design, data analytics, and more in this cutting-edge certificate program. In this program, you'll learn how to optimize Excel workflows, create stunning video content, create captivating graphics, analyze data efficiently, boost workplace productivity, and more with the power of generative AI.
Learn Python, SQL, automation, and machine learning to become a Data Scientist. Gain Python programming, data analysis, SQL querying, and predictive modeling skills. Perfect for beginners, this program prepares you for entry-level data science and Python engineering roles. Unlock high-paying job opportunities in the field of data science.
Gain practical skills in analyzing datasets, building predictive models, and creating AI-powered applications using Python and industry-leading tools.
Create, style, and enhance web apps with AI capabilities. In this advanced Python course, you'll develop a powerful sentiment analysis web application with Flask and the OpenAI API integration and learn how to take your coding projects to the next level with AI.
AI (artificial intelligence) involves the process of simulating human intelligence and behavior using predictive modeling to perform basic tasks. AI represents an area of computer technology that focuses on building devices capable of performing a variety of tasks that normally require human intelligence. Learning AI includes training in data science, data analytics, and machine learning. Because machine learning is related to AI, many assume that the concepts are interchangeable, but they are not. AI involves simulating the way people think through intelligent systems that perform complex tasks the way a person would, while machine learning involves accessing accumulated data to respond to requests by mimicking human behavior. While not the same, the concepts do overlap.
As people have become more dependent on computer technology in virtually every part of their lives, AI has grown into a vital instrument for helping in cloud computing and internet searching. Organizations use AI to integrate data and operate businesses within infrastructures that enable processing workloads relevant to specific industries. Training in AI includes learning data science, Python programming, and data analytics for developing intelligence systems that are often used with machine learning or cloud computing.
Knowledge of artificial intelligence can be applied to working in various industries to process information and perform tasks. There are several areas of business that benefit from AI. For instance, banking, financial services, and technology companies employ Computer Engineers, Data Analysts, Intelligence Developers, and Data Scientists for gathering and analyzing data in fraud detection or financial advising, as well as using machine learning algorithms in risk analysis with stock trading.
The healthcare industry also uses AI for creating algorithms to help with billing. Data Scientists and Data Analysts use AI to handle raw data and look for patterns that might indicate trends and tendencies when presenting findings to help healthcare organizations make informed medical and business decisions.
Skills with AI can also be used to work as a Data Architect who develops strategies and database systems for solving problems in business, science, and education. Machine Learning Engineers apply AI and machine learning algorithms in computer programming, software development, and statistical analysis. Statisticians use AI for gathering, analyzing, and interpreting data to process information across a variety of industries. Analysts also apply AI in data analysis to find relationships and trends within numbers that are critical for making business decisions.
Boston offers a fertile environment for opportunities in technology, especially with renowned schools like MIT close by. Boston provides options for finding work with knowledge in AI that complements several areas of computer technology, such as programming, data analytics, and machine learning. Training for AI can lead to working in industries as diverse as ecommerce, biotech, research and development, and financial services. Therefore, gaining skills in areas involving AI could enhance career opportunities in technology. Here are several categories to consider:
Data analytics in AI helps with automating calculations. Data analytics requires skills for finding patterns that clarify conditions for organizations by examining data patterns and connections within numbers that allow Data Analysts to understand how and why something exists and how a problem might be solved. With AI, data analytics provides predictive analytics for anticipating where information may lead in risk assessment, weather forecasting, or sports analytics.
For anyone considering a career in AI, training in machine learning can provide skills for working in similar areas of computer technology. Machine learning represents a category of artificial intelligence associated with creating programs capable of learning on their own by using data algorithms and processing collected information. Training in Python programming can provide skills for analyzing data using Pandas, NumPy, and Matplotlib, as well as using machine learning algorithms to apply regressions and other methods of statistical analysis for creating predictive models. Working with machine learning applications requires learning concepts such as data mining, robotic control, and autonomous navigation systems.
Anyone considering a career related to artificial intelligence can benefit from training in the Python programming language. Python is a programming language that is easy to read and learn, and it can be used in complex data analysis for handling large datasets. Data Scientists and Data Analysts can apply Python in AI and machine learning for working with mathematical functions, data structures, and data visualization to help analyze information.
Data science can be used to find work in mathematics, computer programming, and AI by providing a comprehensive understanding of how to process data for use with AI in areas like business and digital marketing. Data Scientists and Data Engineers apply data science for advanced techniques with AI and machine learning algorithms to discover patterns within a sea of information. These procedures can lead to results that help Product Managers, Digital Marketers, Business Analysts, or ambitious entrepreneurs achieve their goals in business and careers.
Web Designers must have skills in graphic design and motion graphics for developing the best visual methods for connecting with potential customers. AI can help with creating motion graphics to add dynamic elements to text and graphics on websites, social media platforms, videos, and other visual media for attracting and engaging online users and audiences. Websites, for example, have become a normal way of conducting business and marketing around the world, which has led many companies to employ their own Web Designers and Graphic Designers to help establish a brand identity that sets them apart from competitors. Web Designers use AI to enhance graphics by creating animated images and text that catch the eye of potential customers and help organizations stand out in the internet’s cluttered landscape.
For many, learning AI may not be any more difficult than learning other areas of computer technology. However, the difficulties with learning AI could involve handling machine learning algorithms and other complex procedures related to AI and predictive modeling. Working in AI requires knowledge of algorithms, statistics, and math, as well as an understanding of calculus, algebra, and probability, which many people may find intimidating. Other challenging areas of AI training could include gaining knowledge of Python programming, as well as its frameworks and libraries. Training in AI is typically paired with machine learning to automate tasks through software engineering or data analytics.
The most challenging aspect of learning AI is often dealing with a lot of math and programming languages. There are also inherent challenges related to learning AI that include adapting to today’s ever-evolving digital landscape. Keeping up with constant innovations essential to computer technology requires combining knowledge of machine learning with AI, along with being able to handle tools like Tableau for use in areas such as business or marketing.
Because AI is a complex area of technology that requires knowledge in a wide range of categories, such as programming languages and technical procedures like data science, the time it may take to learn will vary widely. Depending on a person’s goals, mastering AI can take anywhere from a few months to several years. The method of training that people choose will affect how long it will take. This includes whether someone enrolls in a workshop, a bootcamp, a certificate program, or a college degree. Learning AI requires knowledge in math and programming languages, as well as machine learning algorithms. The time it might take to learn how to build AI models can vary widely depending on factors such as a person’s career ambitions, current knowledge and experience, learning goals, and the type of education they pursue. Anyone interested in learning AI can pursue a four-year college degree in computing or enroll in shorter online courses, bootcamps, and certificate programs. Training in AI can lead to becoming a Data Analyst, Research Scientist, Machine Learning Engineer, or Business Intelligence Developer.
There are various formats for learning AI. People can decide to attend in-person, live online, or on-demand courses, bootcamps, and certificate programs in AI to learn data science, programming languages, machine learning, and data analytics. Some people prefer learning inside a classroom with a teacher standing in front of them. For them, there are classes in or near Boston that may offer training in skills related to artificial intelligence inside classrooms.
Conversely, for some people, getting home from work only to have to get back out on the road and into traffic to find a classroom and parking may not be the most appealing way to spend an evening. Live online courses and bootcamps offer hands-on training from expert instructors who can provide the same level of education that a person would get from sitting inside a classroom, without having to leave the comforts of home. Students can choose from shorter virtual learning workshops or take on the challenge of lengthier and more immersive live online bootcamps and certificate programs.
Another option for training would be with on-demand (asynchronous) courses that allow students to learn at their own pace and on their own time. These types of courses offer more flexibility, but do not include live instruction.
Boston is among the most established cities in the United States for research and development related to computer technology, especially with nearby Harvard, Boston College, and MIT helping to create a fertile environment that facilitates advancement in computer technology. Top industries for finding work related to AI and machine learning include biotech, healthcare, transportation, and utilities, as well as government agencies.
Banking and financial services use AI in many ways, including automation, fraud detection, and personalized financial advising. Major institutions such as JPMorgan Chase, Bank of America, and Fidelity Investments apply AI to support loan approval decisions, detect fraudulent transactions, identify cyber-attacks, and deliver targeted marketing. AI also plays a key role in online lending platforms like LendingClub and SoFi, where data-driven models analyze FICO scores and credit bureau data to improve lending decisions.
Artificial intelligence helps banks and financial institutions process massive volumes of transaction data and quickly flag unusual activity linked to fraud. IT security teams use AI-powered tools to monitor network traffic, detect suspicious behavior, and identify abnormal file movement that may indicate a cyber threat. Companies such as PayPal and Visa also rely on predictive analytics and machine learning to analyze customer data, research reports, and marketing metrics to better understand user behavior and emerging business trends.
The healthcare and pharmaceutical industry uses AI and machine learning across research, development, and clinical operations. Boston is home to leading biotech and pharmaceutical companies such as Moderna, Biogen, and Vertex Pharmaceuticals, all of which use AI to predict the safety and effectiveness of drug compounds. These technologies help shorten development timelines and improve decision-making in medicine and life sciences.
Advanced technology plays a critical role in the defense sector, where data analytics and predictive modeling are essential. Companies such as Raytheon Technologies and Lockheed Martin rely on AI and machine learning to operate autonomous systems, including manned and unmanned defense equipment. AI enables military systems to function in extreme environments, enhancing safety, efficiency, and national security.
The insurance industry applies AI to improve operations, manage risk, and market products more effectively. Companies like Liberty Mutual, Allstate, and John Hancock use AI for fraud detection, pricing optimization, underwriting support, and customer segmentation. Insurers also rely on machine learning for risk assessment, lifetime value prediction, claims analysis, and identifying outlier claims, all of which directly impact profitability and long-term financial stability.
Data Analyst
Data Analysts examine structured data to help organizations identify trends and make informed business decisions. In Boston, these professionals commonly support healthcare systems, financial services firms, and research institutions by tracking patient outcomes, operational performance, or financial metrics. Data Analyst salaries in the Boston area typically range from $70,000 to $95,000 per year, with higher earnings for professionals skilled in tools such as SQL, Python, Tableau, or Power BI.
Data Scientist
Data Scientists take analysis a step further by building predictive models and applying machine learning techniques to extract deeper insights from data. In Boston, demand is especially strong in biotech, healthcare, and technology-driven research, where AI supports drug discovery, clinical trials, and advanced analytics. Data Scientists in the region often earn between $100,000 and $140,000 annually, depending on experience and industry, with top salaries going to those with strong programming, statistics, and machine learning expertise.
Machine Learning Engineer
Machine Learning Engineers design, build, and deploy algorithms that enable systems to learn and improve over time. In Boston, they commonly work in biotech, robotics, defense, and advanced manufacturing, collaborating closely with data science and software teams. Their responsibilities include model training, performance optimization, and production deployment. Salaries for Machine Learning Engineers in the Boston area typically range from $120,000 to $160,000 per year, with senior professionals earning more.
AI Engineer
AI Engineers focus on integrating artificial intelligence into real-world applications, using tools such as neural networks, natural language processing (NLP), and deep learning frameworks. In Boston, AI Engineers are in demand at research labs, startups, and established companies across biotech, healthcare, and automation. Compensation generally falls between $125,000 and $165,000 per year, with higher pay for those specializing in areas like computer vision or advanced deep learning.
Business Intelligence (BI) Analyst
Business Intelligence Analysts translate data into actionable insights through dashboards, reports, and data visualizations. While they may not build AI models themselves, BI Analysts often work closely with data scientists and AI teams to guide strategic decisions. In Boston, BI Analysts play an important role in healthcare, finance, education, and technology sectors. Salaries typically range from $75,000 to $105,000 per year, with higher compensation for professionals experienced in SQL, data modeling, and visualization tools such as Tableau, Power BI, or Looker.
Noble Desktop provides a wide range of AI classes, bootcamps, and certificate programs focused on applying artificial intelligence in practical, career-oriented ways. A great entry point for beginners is the AI for Business with ChatGPT & Copilot course, which helps students quickly develop usable AI skills. In this class, participants learn real-world applications of ChatGPT, explore how Microsoft Copilot boosts workplace productivity, and understand how AI tools integrate seamlessly with Office 365.
For learners interested in applying AI in non-technical or non-programming roles, the AI for Business with ChatGPT & Copilot course is also part of Noble’s Generative AI Certificate program. This 78-hour, hands-on certificate covers AI for productivity, marketing, graphic design, video creation, and data analytics. Through live, instructor-led sessions, students gain experience automating routine tasks, improving SEO strategies, and creating compelling visual content using AI-powered tools.
Students aiming for careers in data science or analytics can pursue the AI & Data Science Certificate, a 114-hour program that builds a strong technical foundation in Python, SQL, data visualization, and machine learning. For a limited time, enrollment also includes an extra 30 hours of instruction in Python for AI: Create AI Apps with Flask & OpenAI. Full schedules, course details, and enrollment options can be found in Noble Desktop’s course listings.
Corporate training is a great way to help your company improve skills in today’s technology-dominated workplace. Noble Desktop offers corporate training in AI to prepare your staff to stay competitive in a digital-first world. Training can be delivered onsite at your office or virtually via platforms like Zoom. Companies can also purchase vouchers for public AI courses.
If you want your team to stay ahead through training in generative AI, data analytics, and Python programming to improve workplace efficiency, contact corporate@nobledesktop.com for more information or to schedule a free consultation.