Artificial intelligence, or AI, refers to a set of technologies that machines and computers use to reason, learn, and perform advanced functions that would typically require data at a scale that exceeds what humans are capable of analyzing or human intervention. Computers use AI to understand and translate spoken and written languages, offer recommendations, perform data analysis and deep learning, and offer valuable insights for users.
The term “AI” was originally coined in 1956 by John McCarthy. However, the roots of AI trace back centuries to before computers were invented. The idea to endow objects with artificial life or automate tasks extends back to ancient cultural myths. Yet it wasn’t until Alan Turing created the Turing Machine (a theoretical computing device that could solve any calculable problem when given enough resources and time) in the 1930s that the field of AI began to gain momentum. In the 1950s, Turing proposed the Turing Test, which speculated that once a machine was indistinguishable from a human, it could be deemed “intelligent.” Decades later, in the 2010s, the field of AI underwent rapid growth, which was driven by deep learning.
The field of AI is broad enough to include many disciplines, including linguistics, data analytics, statistics, philosophy, psychology, computer science, and neuroscience. At its core, AI revolves around data usage. When an AI system is given vast stores of data, it can pinpoint patterns and relationships that many humans may miss. The system then works with this information to learn and improve as it’s given more exposure. The learning process usually involves algorithms, which are instructions that structure the decisions AI makes when it analyzes data.
One core subset of AI is machine learning. This involves using either labeled or unlabeled data to train algorithms to recognize the data or provide predictions based on the information it contains. On the other hand, deep learning involves using multi-layered artificial neural networks to mimic the way the human brain processes information. The more an AI system learns and adapts, the better it becomes at tasks like recognizing images and translating languages.
What Can You Do with AI Training?
AI training is a great way to learn the problem-solving skills to help you excel in an ever-expanding digital landscape. You can put your AI training to use performing quick data analysis on huge volumes of data and identify patterns contained in the information. The insights this process provides can spur innovation and improve operations in many professional environments. AI can be used to develop self-driving cars that independently navigate roads and make decisions. It’s also used to create and maintain advanced cybersecurity systems that protect organizations’ data. AI also can also perform speech and facial recognition. Those who are familiar with AI can use their skills to train digital assistants to make schedules, provide recommendations to users, and answer questions. AI chatbots ensure that customers receive immediate information, which leads to better service. This technology also helps recommendation engines learn from user preferences to provide better recommendations.
AI training provides a great opportunity to blend technical knowledge with creativity. Because this field is experiencing a rapid evolution, individuals who can find innovative ways to solve challenging problems are in-demand. Not only does AI training require knowledge of algorithms and data structures, but it also requires that learners be able to think outside the box. AI algorithms that are used in music can be trained to compose new pieces or modify those that exist. Within the digital art field, AI is a powerful tool for creative-minded individuals to create intricate designs and patterns that would be extremely time-consuming to complete manually. Even those who focus on research and development benefit greatly from AI training. AI-powered robots are involved with outer-space exploration. Machine learning plays an integral role in current medical research. Businesses work with automation to optimize their routine processes and tasks in customer service or HR. This significantly improves efficiency while cutting down on operational costs.
What Will I Learn in an AI Class?
No two AI courses are the same in terms of the content they teach. The material that’s taught varies depending on the scope of instruction provided, the program’s length, and its difficulty level. However, most beginner-friendly courses provide learners with instruction on core AI topics and skills, including data science, deep learning, machine learning, coding, ethical AI practices, and natural language processing.
Data Science
Because data science is a foundational element for AI, most programs teach this subject. Most AI applications draw from data analysis and manipulation techniques from data science. Learning data science basics is a great way to prepare to create and train AI models and automate difficult data analysis tasks.
Deep Learning
Another topic students of AI are likely to encounter is deep learning. This is a form of machine learning in which artificial neural networks that use multiple processing layers help users access increasingly higher levels of information contained in the data. Deep learning is used in fraud detection, facial recognition, and predictive analytics.
Machine Learning
Machine learning is another core subject most AI courses teach. Machine learning entails creating and implementing computer systems capable of learning and adapting, even without the help of explicit instructions. These systems draw from algorithms and statistical models to spot and analyze patterns in data and then offer inferences based on these patterns.
Coding
One of the most fundamental parts of learning AI is computer programming training. Programming skills are essential to designing and implementing AI systems. Developers work with coding languages to create algorithms, train models, and convey the logic that drives the machine-learning process so computers can make decisions that are backed by data. Training often covers one or multiple coding languages. Python is the most commonly taught programming language in AI because it has vast libraries, is considered easier to learn than other programming languages, and has applications for deep learning, computer vision, and machine learning. Some courses also teach C++, which is a popular language for powering the back-end of machine-learning libraries. Programs also often include instruction on Java, an object-oriented coding language that is stable enough to handle large datasets. R, too, is taught in some courses because it can be used to create AI models that are based on advanced data analysis.
Ethical AI Practices
In addition to hard skills like computer programming and natural language processing, students who study AI are likely to gain training in the ethics of developing and deploying AI. As AI becomes increasingly prevalent in society, it’s essential to learn how to use this evolving technology responsibly. This includes respecting data privacy and exploring the potential AI has to violate personal privacy. Instruction is usually provided on transparency and accountability, including who is accountable for the decisions AI systems make and the ramifications of these decisions.
Natural Language Processing
Natural language processing is a type of computer science that’s commonly taught in AI programs. Natural language processing involves computers being trained to process and understand both written and spoken human language. This provides them with a way to “read” and interpret text in a way that is similar to the human brain.
How Hard is It to Learn AI?
Before you commit to learning AI, you may be curious about how hard it will be. Perhaps you’ve heard that you have to be a math wiz or expert programmer to work with AI. Although studying AI can pose challenges for some individuals because it requires knowledge of complex mathematical concepts and coding, learning AI is an achievable goal for anyone willing to devote their time to training and practice.
The difficulty level associated with learning AI depends on several subjective factors such as your prior experience in related fields like data science or computer programming, how quickly you learn technical concepts, and the type of training you select. Most individuals who opt for formal training and spend time practicing the skills they’re taught will find that learning AI basics is relatively easy. This includes basic algorithms and coding. Learners should keep in mind that to succeed in this field, they should have a strong grasp of database libraries and frameworks, one or more programming languages, and mathematics. Advanced AI concepts such as deep learning and machine learning will require additional time and effort to master.
Those who are interested in learning AI for work-related reasons will need to learn advanced AI concepts. This process typically takes a substantial amount of effort and time compared to simply studying basics.
What Are the Most Challenging Parts of Learning AI?
Each learner will encounter their own hurdles when learning AI. Generally speaking, the most challenging part of the process for most students is fully grasping the necessary mathematical concepts. Those who aren’t keen on math may find this process especially challenging since learning AI requires knowledge of probability, statistics, linear algebra, and calculus. Another difficult aspect of learning AI is studying machine learning because it requires understanding algorithms. Some learners also may find it difficult to learn the range of programming languages they’ll need to work with AI. The best way to expedite the AI learning process and ensure you’re gaining the training you need is to enroll in a live course or training program that provides hands-on instruction in a small class environment.
How Long Does It Take to Learn AI?
The time required to learn AI varies from one learner to the next and depends on a host of factors. Those who already know one or more coding languages and who have a solid background in math will find the learning process much easier (and faster) than individuals who have to start from scratch. Similarly, the learning method selected will also greatly affect the speed with which you learn AI. Generally speaking, learning AI in its entirety can take between several months to several years. Those interested in becoming comfortable developing and using AI will likely need several years to gain this training. Because AI is such a layered, complex subject, learners should approach their studies with realistic expectations. Live training provides a way for students to stay abreast of industry standards and best practices, receive individualized support and feedback, and ensure they’re on the right track.
Several additional factors can influence the speed at which you learn AI. If you intend to apply your training in a professional setting, you’ll have to devote more time to study and practice. On the other hand, if you’re learning AI for personal reasons, you can spend far less time on training. Additionally, because of how many skills are required to work with AI, each learner will differ in terms of their specific knowledge base. For example, you may be much more comfortable with math than Python or may know linear algebra but not really recall statistics that well. Finally, your availability is another key factor that will affect how long it takes you to learn AI. If you work full-time or have a busy personal life, you may have much less time to devote to training and studies than those who have fewer scheduling constraints.
Should I Learn AI in Person or Online?
Once you’ve decided to study AI, you may wonder if it’s better to choose in-person or online training. Live training is available in-person at training facilities in Orlando, as well as online using a teleconferencing platform. Students can also opt for on-demand AI courses, which are self-paced. Read on to explore the benefits and drawbacks of each type of study.
In-Person AI Training
The most engaging and interactive way to learn AI is through in-person coursework. This type of training takes place in a computer lab in a training facility that’s located in or near Orlando. The lab provides students with access to computers that have all the essential, most up-to-date AI tools and software installed and ready to use. Not only do students benefit from learning from an expert instructor who’s there to offer individualized support and share their industry knowledge, but also the support of other students in their cohort. If in-person AI classes sound like a good option for you, keep in mind that you will need to have access to a reliable form of transportation to attend training. For some learners such as those who live far from a training center or don’t have a way to commute to class, in-person study may not be possible.
Live Online AI Training
One popular alternative to in-person AI training is live online coursework. This type of coursework offers learners many of the same educational benefits and learning outcomes as in-person study. With live online classes, students attend classes using a live teleconferencing platform like Zoom, which allows them to connect in real-time with an expert instructor. Each participant can ask questions at the moment and receive immediate feedback. Students can even give the instructor permission to share their screen for more individualized assistance. One of the main benefits of live online study is that learners never have to battle rush-hour traffic in Orlando to attend class or waste money on tolls and parking. All coursework can be completed remotely from any location with an internet connection.
Because live online AI classes are taught in real-time, students who wish to enroll should have schedules in which they’re available to attend courses that meet regularly, often multiple times a week. For learners who work full-time or have personal commitments outside of work that require a good portion of their time, live online study may pose challenges.
On-Demand AI Training
The most flexible way to study AI is through on-demand coursework. Whereas live classes take place in real-time, on-demand courses are pre-recorded and placed online. Students can decide when it is best to access course content and complete lessons. This type of training puts the learner in control of their learning speed. Students can pause, rewind, and rewatch entire lessons at their discretion to ensure they’re fully grasping the material. They can decide to spend an entire weekend learning Python programming basics or spread this training out over several weeks after work, depending on their availability. One important consideration of on-demand AI coursework is that no instructor is available. It’s up to each student to find answers on their own to any questions they have.
Because AI is such a broad field of study that spans several disciplines, this type of training may be difficult for those new to the technical concepts, mathematical skills, and programming languages being taught. Learners who get the most out of on-demand training are typically self-motivated learners who can find supplemental resources when necessary to make sure they’re understanding the material being presented.
Can I Learn AI Free Online?
Before you pay money to attend an AI course, you may wonder if any free learning options are available. There are several options available that can help you learn AI:
- In-person AI resources can be a good place to start learning AI. Learners can find brochures, research papers, textbooks, and even lecture series on AI or adjacent fields at most libraries in Orlando. Although the content will vary from place to place, there is typically some form of AI training content available for free in libraries.
- Many local Orlando career centers provide seminars, workshops, lectures, and local events pertaining to AI. While not all locations have a career center nearby, these can be valuable resources for preparing for interviews, attending job fairs, or learning more about the field of AI.
- Many online AI resources are available for learners at all levels. While the sheer volume of free online content can be a positive, it can be hard to know which resources are reputable and current, and which are less reliable. Free online AI resources take many forms. Learners can find information on social media, discussion boards, websites, and video channels like YouTube playlists. Many AI organizations also provide official websites that contain AI information. AI experts often share their insights on social media platforms like Facebook, TikTok, and LinkedIn. Forums, chatrooms, and blogs are also available for learners to share their stories with other learners and experts. Additionally, some training centers or educational platforms like Udemy offer free resources like articles, videos, or lectures.
- Noble Desktop, an educational provider based in New York City, has free webinars pertaining to several AI skills. Learners can explore Python basics in Noble’s Intro to Python Fundamentals. This pre-recorded lecture provides training in concepts like how to install Python, write basic code, and use integers, strings, and floats. Noble also has a free Machine Learning Tutorial and a comprehensive guide that helps students learn Python for data science. Noble also has a YouTube channel devoted to AI skills like data science and Python.
While free AI resources can provide you with a basic understanding of the concepts and terminology used in this field, most learners will not find them sufficient to provide a well-rounded education in AI. Free resources vary too much in quality, credibility, scope, and content to make them a reliable way to fully learn AI. They also don’t provide learners with feedback on their work. Since no instructor is available in these resources, students may find that they have to spend more time looking up answers or troubleshooting techniques with free content. Individuals who want to use AI for work-related reasons will need to have an advanced understanding of this field, which will usually require more structured, live training beyond just the fundamentals.
What Should I Learn Alongside AI?
Students of AI can select from several related fields to supplement their training. Because of how many skills are required to succeed in AI, learners will benefit from knowledge of the following fields:
- Computer programming skills are essential in AI. Depending on the program you’re enrolled in, you may explore one or more coding languages, including Python. However, if you want to supplement your training, you may also wish to learn C++ to build high-performing AI apps that require memory and speed control. You also may wish to work with Java because of its extensive range of libraries. R training is useful for analyzing and visualizing data, as well as modeling this information. List was one of the first programming languages used in AI; students may want to explore it for use with natural language processing and symbolic reasoning.
- Mathematics skills are a must in AI. If you don’t come from a math-heavy background, or if there are gaps in your knowledge base, you will likely need to brush up on calculus, linear algebra, and probability, which are essential for understanding how AI algorithms operate.
- Knowledge of data science is also a staple of AI. Students may wish to review core data science skills and concepts to supplement their studies, including how to gather, clean, analyze, and visualize data, which are essential skills for prepping data to train AI models.
- Some AI students may opt to learn machine learning as part of their training. Knowledge of various machine learning algorithms provides the skills needed to help computers learn from data without being given explicit instructions.
- Natural language processing skills are another good supplement to AI training. Some programs teach students how to analyze and interpret human language using AI techniques, whereas other coursework may not include this type of training.
- Depending on which field you hope to use your AI training in, domain-specific knowledge may also be necessary. This includes training in fields like robotics, finance, or healthcare.
- If the coursework in AI you select doesn’t include instruction on the ethics in this field, it’s a good idea to explore the possible ethical concerns that are involved with developing and deploying AI.
Industries That Use AI
Training in artificial intelligence is useful in many prominent Orlando industries, including healthcare, advanced manufacturing, finance, and nonprofits. Read on to take a closer look at the role AI plays in each of the city’s sectors.
Healthcare
One of the main Orlando industries is healthcare. Orlando is home to some of the country’s largest health systems, particularly those that focus on medical innovation and life sciences. Orlando Health is one of Florida’s main health systems and has 16 ERs and hospitals in the region. Currently, nearly 258,000 Orlando residents are employed in healthcare in the region. Within the field of healthcare, AI training is used to provide patience with personalized treatment plans. It also has applications for analyzing medical imaging, assisting with diagnoses, and discovering new drugs and treatment options.
Advanced Manufacturing
Another major industry in Orlando is advanced manufacturing. The city has the largest number of manufacturing jobs in Florida and plays an integral role in the local economy. Many advanced manufacturing initiatives are underway in this region in areas like defense, simulation, aerospace, and biotechnology. Those employed in advanced manufacturing rely on AI for tasks like quality control, new product design, production line optimization, and predictive maintenance.
Finance
Orlando’s finance sector is another prominent sector in the city. It includes banks, insurance providers, and consulting companies that provide financial counseling and services to individuals and businesses. Florida is currently ranked third in the US in terms of the concentration of insurance companies and banks. Companies like Travel + Leisure, AAA, and Darden Restaurants are located in this region. Those who work in finance-related careers in Orlando benefit from AI training because it can be used to automate data entry, process invoices, and analyze financial data. It also has applications for risk assessment, fraud detection, algorithmic trading, and customer service chatbots.
Nonprofits
Another thriving industry in Orlando is the nonprofit sector. There are currently more than 14,000 nonprofits in the greater metro area. These organizations employ a workforce of 160,000 locals and generate about $24 billion in yearly revenue. Within the nonprofit sector, AI helps organizations with fundraising initiatives. It can be used to segment audiences for targeted outreach campaigns, identify prospective donors, analyze vast datasets, and create personalized communications with donors. It also assists with automating repetitive tasks, including data entry.
AI Job Titles and Salaries
Regardless of your career path, AI training can lead to a high-paying job in many fields. AI is one of the fastest-growing job markets in the US. Companies of all sizes and in many industries are actively seeking professionals who can use their AI training to streamline operations, drive innovation, and help them have a cutting edge over competitors. Those who have AI skills can put their knowledge to use in a variety of career paths in Orlando, including data science, engineering, and machine learning. Read on to learn more about the basic job requirements for each role and the salary ranges for these professions.
Data Scientist
Data Scientists are involved with gathering, organizing, and analyzing huge datasets. The data analytics process unearths insights that can help organizations like businesses and nonprofits make better decisions. These professionals look for data trends and share their findings with relevant stakeholders. They also work with models and algorithms to simplify and mine data so the recommendations they provide are data-driven. The average salary range for a Data Scientist in Orlando is $144,000-$154,000 a year.
Data Engineer
Those who are employed as Data Engineers in Orlando use their skills to design data infrastructures and organize data into systems that help Data Scientists with analysis. These individuals may choose to focus their efforts on databases, platforms, pipelines, infrastructure, or warehouses. Some work on AI-specific projects, whereas others devote their training to IT, healthcare, software, transportation, marketing, or retail. Data Engineers who work in Orlando earn an average salary of $113,000-$123,000.
Machine Learning Engineer
Machine Learning Engineers are involved with designing, building, and maintaining AI systems. These systems learn from data and use algorithms to automate repetitive tasks and provide predictions based on the information these data contain. On a daily basis, Machine Learning Engineers create machine learning models and deploy them so that real-world problems can be solved. Machine Learning Engineers who work in Orlando can expect to earn about $144,000-$154,000 annually.
AI Classes Near Me
If you’re interested in finding AI coursework, Noble Desktop’s Classes Near Me tool can help you search for AI courses in Orlando. Training options are available in-person and online and are open to learners at all levels, including those who are just getting started with AI.
Noble Desktop offers several AI-related courses. Each program is available in-person in NYC and live online and includes a free retake option for up to a year. Immersive AI training is available from Noble Desktop in its Generative AI Certificate. This intensive program prepares learners to apply their AI training in a variety of fields such as data analytics, graphic design, marketing, and finance. Those enrolled explore ways to increase workplace productivity using AI, as well as create marketing content like motion graphics, graphic design, and videos. Coursework also covers data analytics and Excel. No prior programming experience is necessary to enroll.
Noble also has a Python Machine Learning Bootcamp for those who want to explore essential machine learning concepts. Those interested in enrolling should have prior training with Python and be familiar with its data science libraries like NumPy and Pandas. This bootcamp begins by teaching students about logistic and linear regression analysis. Participants then study algorithms and theories that drive them, including how decision trees differ from random forest trees. Coursework focuses on how students can apply their training in the real-world in fields like data science and machine learning. Supplemental 1-on-1 bonus training is included with tuition.
Noble also offers a Data Science & AI Certificate, which is intended for those seeking intensive, in-depth training on a range of data science skills and tools. This comprehensive program covers programming languages like Python and SQL, as well as automation, data analysis, predictive modeling, and machine learning. Graduates of this course have the training needed to pursue an entry-level Python engineering or data science career. Supplemental 1-on-1 mentoring is included with tuition.
Intermediate-level instruction is offered by General Assembly in its Data Science Bootcamp. This program teaches students the techniques and skills necessary to communicate and solve problems like an Analyst. Students work with industry-standard tools and coding languages like Excel, Power BI, Python, SQL, and Tableau. General Assembly also has a beginner-friendly Data Analytics Bootcamp, which is intended to prepare participants for data analytics jobs. Learners work with Power BI, Excel, SQL, and Python during this hands-on program. These classes are available in-person in Orlando and live online.
In UCF Boot Camps Digital Marketing Boot Camp, learners spend several months exploring the basics of digital marketing. They work with tools like HTML and CSS, Mailchimp, CRMs, Facebook Insights, and Google Analytics to develop their digital marketing skills. Instruction is provided on content and brand strategy, automation, lead generation, conversion tracking, and backlinking. This program is taught in-person in Orlando.
Orlando residents can prepare to take the Certified Information Systems Security Professional certification exam by enrolling in Certstaffix Training’s CISSP: Certified Information Systems Security Professional class. During this program, learners explore topics like risk and security management, security engineering, security operations, access and identity management, and software development security. Instruction is available live online; participants can complete their training remotely or use the computer lab that’s provided in-person in Winter Park.
AI Corporate Training
Are you an Orlando-based employer who feels that their employees would benefit from studying artificial intelligence? If so, Noble Desktop can provide corporate and onsite AI training options for some or all of those at your workplace. Training is available for employees at all levels, including those who have no prior experience with AI concepts or tools. You can select from AI training options that focus on Excel, generative AI with ChatGPT, data analytics, Microsoft Copilot, marketing, video, graphic design, motion graphics, or Python. Training options are available in-person at Noble’s headquarters in Midtown Manhattan, live online, and directly at your workplace in Orlando.
Noble offers discounts for employers interested in purchasing bulk enrollment vouchers for regular enrollment classes. Your employees can attend these classes outside of business hours, which makes them a great option for those who work full-time and still want to learn AI. Noble can also customize the AI training it provides your employees so that you’re sure the skills they’re learning are in line with your corporate organization’s needs.
If you’d like to find out more about the various corporate training options in AI available from Noble Desktop, please don’t hesitate to contact Noble for more information.