Top 4 AI Bootcamps: Options, Costs, and Alternatives

An AI bootcamp is an intensive, short-term educational program designed to equip individuals with the skills they need to enter or advance in the field of AI. Unlike traditional degree programs that may take years to complete, bootcamps are typically designed as accelerated learning paths. The goal is to provide a fast-paced, focused curriculum that covers essential AI topics and tools, enabling participants to quickly gain practical skills.

If you're considering enrolling in a machine learning bootcamp, this guide is for you. In the following sections, I will provide a comprehensive overview of AI bootcamps, covering the most frequently asked questions and advancing a list of top machine learning bootcamps, as well as some top machine learning bootcamp alternatives offered on DataCamp.

Why Choose an AI Bootcamp?

There are many reasons why people choose an AI bootcamp over a traditional degree program:

• Fast certification. Bootcamps students can obtain a professional certification in a short amount of time, typically in a matter of weeks or months.
• Career support. Bootcamps offer career services such as resume assistance, mock interviews, networking events, and partnerships with employers to help during job search.
• Flexible schedules. Bootcamps offer flexible options to fit different schedules, including part-time, online, or in-person. This allows learners to conciliate their personal circumstances while still gaining new skills.
• Cost-effective. Bootcamp tuition is typically much lower than the cost of a four-year degree in computer science or data science, which can make it a more financially accessible option for some individuals. However, costs still tend to be higher than some other alternatives. 

Choosing The Right AI Bootcamp For You

Although less costly and lengthy than traditional degrees, an AI bootcamp can still be a big investment of time and money, so it's important to determine if it's the right fit for your goals. 

Before committing to a bootcamp, you should build some of the relevant skills first. A great option for this is our AI Fundamentals Skill Track, a 6-course program that will help you discover the basics of AI, including actionable knowledge on popular AI topics like ChatGPT, large language models, and generative AI.

If you are convinced to enroll in an AI bootcamp, you should always consider the following factors: 

• Your goals. Are you considering a career change or looking to enhance your skills? Define your goals to determine if a bootcamp, degree, or online learning is the best option for you. There is no one-size-fits-all approach to data science, so it's important to assess your specific situation before deciding on an intensive bootcamp.
• Curriculum coverage. AI is a demanding domain that –if you want to learn the technical aspects and how to build your own models– requires a background in Python, SQL, and statistics. If you don’t have this background, you should first focus on building fundamental programming skills.
• Learning format. Depending on your circumstances, an online program may be better than an in-person program.
• Time schedule. Depending on your situation, a part-time program may be better than a full-time program.
• Mentorship opportunities. Some bootcamp offer mentorship opportunities. This is a cool feature, especially if you are switching careers and need someone to guide you through this new field and market.
• Job guarantees. Some bootcamp have arrangements with companies to provide internships and even jobs after completing the bootcamp. 

What Will You Learn?

While the curriculum for machine learning bootcamps can vary depending on the program, all of them should cover at least the following topics:

• AI and machine learning fundamentals. Covering what AI and machine learning are, how they’re relevant in today’s economy, and how the field has evolved.
• Types of machine learning. When speaking about AI, we are most of the time speaking about machine learning, a subset of AI that studies how machines can learn from data without being explicitly programmed. Machine learning can be classified into three types:
• Supervised learning is the most common type of machine learning. In this approach, the model is trained on a labeled dataset. 
• Unsupervised learning, on the other hand, involves training the model on an unlabeled dataset. The model is left to find patterns and relationships in the data on its own.
• Reinforcement learning is where an agent learns to make decisions by interacting with its environment. The agent is rewarded or penalized (with points) for the actions it takes, and its goal is to maximize the total reward.
• Types of problems in machine learning. Most common machine learning problems can be classified into three groups:
• Classification. Predicting an event or class of the data, for example, classifying an email as spam or not.
• Regression. In regression problems, the output is continuous, for example predicting the temperature in a city for the next day.
• Clustering. In clustering problems, the goal is to classify data into n-number of classes, where n is not predefined, for example, clustering customers into similar groups based on their demographics, interests, and purchase history.
• Common machine learning algorithms. An overview of the most common learning algorithms for each machine learning problem and how to implement them with popular Python packages like scikit-learn.
• Deep learning fundamentals. What deep learning is and how this branch of machine learning is rapidly changing the world.
• Neural networks. What neural networks are, and how to use and build them with popular frameworks, such as PyTorch and TensorFlow.

This is the minimum content an AI bootcamp should have. However, artificial intelligence is a rich and rapidly evolving field. Depending on your interest, you could also look for more specialized programs. For example, you may be interested in a program focused on natural language processing or image processing. 

You may even be looking for a bootcamp that focuses on generative AI, a branch based on deep learning that is booming following the launch of ChatGPT.

The 4 Best AI Bootcamps

Below, we’ve outline a list of AI bootcamps and bootcamp-like options that offer high-quality curriculums and learning experiences:

1. Clarusway Machine Learning Course 

Clarusway’s machine learning program empowers students to become versatile AI professionals. You’ll not only master popular machine learning algorithms and frameworks with Python, but also delve into the fascinating world of Generative AI.

In addition to the online curriculum, you will have the opportunity to practice what you’ve learned with +10 hands-on projects and +3 capstone projects at the end of the course.

Who it's for: Suitable for those with a solid background in data analysis with Python, who can commit full-time for 13 weeks.

What you'll learn: The Machine Learning Program is meant to equip you with the advanced skills necessary to pursue a career as a machine learning engineer. 

Cost: $6,000, with flexible financing options. 

Length:  13 weeks

2. UC San Diego ML Engineering & AI Bootcamp

In this online, 9-month program, you will gain the skills and knowledge needed to excel in the exciting field of machine learning and AI. The course is designed to take you from a beginner to a confident practitioner. You'll start with an introduction to basic ML algorithms and quickly advance to topics like deep learning, large language models, and generative AI, as well as AI ethics.

The program comes with hands-on projects, a capstone project and human support throughout the course, including 1:1 mentorship, mentor calls and career services.

Who it's for: Suitable for those with a solid background in object-oriented programming (prospective students will complete a technical skills survey during the application process) who can commit at least 15 hours per week.

What you'll learn: The Machine Learning & AI Program is meant to equip you with the advanced skills necessary to pursue a career as a machine learning engineer. 

Cost: $13,950, with flexible financing options and scholarships

Length: 9 months.

3. 4Geeks Academy Applied Artificial Intelligence Course

This comprehensive Applied AI Course is tailored for professionals eager to leverage the power of machine learning and generative AI within their current roles. Over six dynamic weeks, you’ll gain a deep understanding of AI and its real-world applications. From understanding the various types of generative AI to mastering key elements like context, prompts, and models, this course will equip you with essential tools and best practices to optimize AI integration.

The program comes with a range of hands-on projects and interactive sessions, and can be done online, hybrid or in person. It includes lifelong coding mentorship, unlimited career support, and a job guarantee within 6 months.

Who it's for: Everyone can access this bootcamp, as no previous experience is required. 

What you'll learn: AI fundamentals and a deep dive into generative AI and how to leverage its power. 

Cost: $3,500, with flexible financing options and scholarships

Length: 6 weeks.

4. Springboard Machine Learning & AI Bootcamp

Springboard Machine Learning & AI Bootcamp is designed for those interested in becoming machine learning engineers. Developed in partnership with the University of Massachusetts Global, this online, 9-month program is structured to take you from a beginner to a confident practitioner in the field of machine learning. You'll embark on your journey with an introduction to fundamental ML algorithms and quickly progress to cutting-edge topics like large language models and generative AI.

The program comes with regular 1:1 guidance from an industry mentor, hands-on mini-projects and a capstone project, and career support services. 

Who it's for: Suitable for those with a solid background in data analysis with Python, who can commit 15-20 hours per week.

What you'll learn: The skills to become a solid confident. learning engineers

Cost: $9,000, with flexible financing options and scholarships

Length. 9 months.

Bootcamps compared

We’ve collated the information about the top AI bootcamps into a table for quick reference: 

The Bootcamp Experience: What to Expect

Every AI bootcamp offers a different learning experience. However, there are certain elements you can expect in most of them.

Below, you can find a detailed walkthrough of a typical bootcamp journey:

• First contact with the support team. Before applying for a bootcamp, you will normally have a preliminary conversation with someone from the support team, who will give you additional details on the program. This is a great moment to get an idea and a vibe of what you can expect. Don’t be shy; ask all your questions and share your potential concerns. 
• Technical skill survey. An important step before applying for a master's is the technical skill survey. This is especially important in these bootcamps, for AI is a complex topic that requires a minimum level of programming, statistics, and so on. If you are just starting your data science journey, maybe, an AI bootcamp is too ambitious for now. 
• Application. Time for submitting your application. The process should be straightforward. Once you sign the contract, you can expect a welcoming box or email with all the details of the program (dates, curriculum, contacts, available services, and so on).
• The bootcamp starts. Once the bootcamp starts, be ready for a hectic learning experience. Bootcamps are designed as accelerated learning pathways. Things will go very fast in the following weeks or months. You will meet new topics and instructors every week. With little time to digest all the information and complete the cascade of assignments, it’s possible that you will feel overwhelmed at some point. Don’t worry. This is part of the bootcamp experience, and, at the end of the day, it works. 
• Mentorship. The time during the bootcamp can be stressful. Luckily, you won’t be alone. In addition to your fellow students, you will normally be assigned a mentor to support you along the way. This is the contact person for both technical and non-technique inquiries. Rely on them, they will be very happy to help.
• Career support. Some programs also offer career support. This translates into job hunting seminars, tips for CV drafting, direct access to job interviews or one-to-one sessions with an HR specialist with close bonds with the industry.  
• Final project. The best way to learn machine learning is by doing. Most bootcamp include a final project where you will have to solve a specific AI project. This is a great moment to apply what you have learned in the previous weeks.  
• Graduation. In the blink of an eye, the bootcamp will be over. In the case of in-person programs, you can expect a graduation ceremony. 

Financing Your Education

AI bootcamps are less expensive than a traditional 4-year degree, but they can still represent an important investment. Every student comes with unique personal circumstances. Your economic situation and needs are something you should definitely speak about in your first conversation with the support time. They will do their best to find a way to accommodate your needs. 

If you are unable to pay the complete tuition cost at once, the bootcamp probably offers you other financing options, including upfront payments, monthly installments, tuition deferral options, or student loans.

Moreover, many bootcamps offer scholarships and financial aid, especially for underrepresented groups in tech. Again, don’t miss the opportunity to discuss potential funding that may apply to you before submitting your application.

Alternatives to Machine Learning Bootcamps

While AI bootcamps offer an intensive route to skill acquisition, they're not the only (or always the best) educational pathway available. Here are some alternatives: 

• Online platforms like DataCamp. Ideal for those seeking flexibility and lower costs. DataCamp offers specialized tracks in areas like data analysis and AI, complete with interactive exercises, real-world projects, and a thriving community. This allows for self-paced, comprehensive learning at a fraction of the cost of a bootcamp. 
• University degrees. Suitable for those looking for a deeper, more theoretical understanding of data science and AI. University programs offer a broad curriculum and the opportunity for specialized research. 
• Self-study. Best for highly motivated individuals who are comfortable learning from books, online tutorials, and free courses. This is generally the most budget-friendly option but requires a high level of self-discipline.

Top DataCamp Career Tracks - The Perfect AI Bootcamp Alternative

Some of the best alternatives to AI bootcamps are DataCamp’s career and skill tracks. These educational programs can provide you with the skills, knowledge, and hands-on experience to kick-start your career in AI.

Not only are these tracks self-paced, but they are completely free as part of a DataCamp Premium subscription, starting from as little as $14 per month. You can even gain a AI Fundamentals certification, giving you an industry-recognized qualification.