3 Best Machine Learning Bootcamps in San Diego
Beginning your education in machine learning can be an exciting yet daunting task. It’s a career transition that should lead to a six-figure salary, but to get those kinds of results, you need to start correctly—and that means choosing a quality bootcamp provider.
A quick search shows that over 300 different schools offer bootcamps and courses in machine learning and it’s easy to feel overwhelmed by the sheer number of choices. In this article, we aim to simplify the decision-making process by exploring the best machine learning bootcamps in San Diego.
Find out everything you need to know about curriculum, pricing, support, and schedules, as well as how to weigh the importance of each as you make your decision.
Best Machine Learning Bootcamps in San Diego
Here is our curated list of the best machine learning bootcamps in San Diego.
UC San Diego Extended Studies
The Machine Learning Engineering and AI Bootcamp at UC San Diego is a completely online and flexible course that you take with a cohort of other students. There are no live classes, but you will have access to an online community filled with other students, as well as a weekly 1-on-1 call with an industry expert mentor.
Career support also includes 1-on-1 guidance, where you can practice your interview skills and create a unique job strategy. If you’re struggling with a technical problem during the week, you can also take advantage of unlimited on-demand calls with other mentors to help you get the problem solved.
Some of the topics included in the UC San Diego bootcamp are:
Machine learning models
The machine learning engineering stack
Machine learning models at scale in production
Deploying machine learning systems
Working with data
4.5 out of 5 from Course Report
You can complete the course in nine months by studying 15 hours per week. Or, you can put more time in and finish faster.
Cost when paid in full and upfront: $9,900
Installment payments: Five payments of $2,790
Student loans and scholarships are also available
The Caltech Artificial Intelligence and Machine Learning Bootcamp is delivered in partnership with IBM and the learning platform Simplilearn. The course combines both live instructor-led sessions using virtual-classroom software and on-demand content for independent study.
As a student, you’ll have access to a forum to communicate and collaborate with other students in your cohort. You will also have access to personalized career guidance provided by Simplilearn. The curriculum includes more than 25 hands-on projects as well as three capstone projects you can use in your professional portfolio.
There are some eligibility requirements for this bootcamp: students need to be over 18 years old, hold a high school diploma or equivalent, and have some experience in programming and mathematics. Caltech also recommends at least two years of formal work experience. The course covers a wide range of in-demand skills including:
Natural language processing
4.33 out of 5 from Course Report
Hybrid live instruction and on-demand content
Includes IBM certification badges
Career support from Simplilearn
The bootcamp runs for around seven months and is delivered on a part-time schedule.
The upfront fee for the entire course is $10,000.
The Data Science and Machine Learning Bootcamp at 4Geeks Academy is a part-time course delivered through three live classes per week. Classes are limited to just 12 students, meaning everyone has a chance to interact with the instructor and ask questions during a live session.
The course includes a job guarantee, meaning that you’ll get a full tuition refund if you don’t land a machine learning job within 180 days of graduation. To make sure you do get that job, however, 4Geeks Academy offers career support and gives students access to a network of 5,000 hiring partners to help shorten the job searching process.
Before beginning the course, students will complete two weeks of pre-work on the Python programming language fundamentals and then dive right into the first Python module covering libraries like Numpy, Pandas, and Matplotlib. Other topics covered during the curriculum include:
Statistics and linear algebra
Collecting and storing data
Capstone machine learning project
4.86 out of 5 from Course Report
Class size of just 12 people
No previous experience required
Hiring network with over 5,000 partners
The course lasts 16 weeks, with three live classes per week.
Upfront discount: $9,999
$4000 scholarship available with the Clark University TechBoost Fund
Financed loans are available, which can be paid back in three to five years
How Do You Choose a Machine Learning Bootcamp in San Diego?
Bootcamps are a big investment of both time and money—in that sense, it’s not so different from picking a college to attend. With so much on the line, it’s important to think carefully about exactly what you want to gain from your bootcamp and what features are most important to you. Here are some of the most important things to consider.
The title of a bootcamp only gives you a slight glimpse into what it will actually teach you. You also need to know whether the curriculum is designed for beginners or more advanced learners, and what kind of career role the course is aimed toward. Some machine learning courses also require experience in software engineering, statistics, linear algebra, or calculus to be eligible for enrollment.
Once you’ve checked these basic points, you need to look at the full course curriculum. A good way to check if the curriculum is well-matched to your desired role is to check the skills covered by the course against the skills required by job posts for your chosen role.
Here are some important keywords to look out for when you look through a machine learning curriculum:
Trees and boosting
Time series analysis
Advanced ML deployment
Natural language processing
Image processing and computer vision
Instructor Credibility and Expertise
A good bootcamp hires instructors with both expertise in the subject matter and ongoing experience in the industry. This is because bootcamp curriculums aren’t about theory and academics in the way that a college course is—they’re about teaching students the practicalities of a machine learning job and the skills you need to thrive in one.
This means that the instructors and mentors themselves also need to know what it’s like to work as a machine learning engineer today. Most schools introduce their instructors on the course page and tell you about their experience, so make sure to read it through.
Investing in your career is always worthwhile, but it’s important to make sure you’re getting your money’s worth from your course. Many bootcamps don’t want to simply reject potential students because they can’t pay upfront, so they implement alternative payment options like monthly installments, ISAs, loans, and scholarships.
Hands-On Experience, Training, and Practical Projects
As mentioned above, bootcamps are all about learning how to be a machine learning engineer and mastering the daily tasks you’ll have on the job. The best way to prepare yourself for this is with a project-based curriculum.
It doesn’t matter whether the school offers part-time programs or full-time programs, both can have project-based curriculums. It simply means that you learn through doing. You study a set of principles, and then you apply them to a common machine learning task.
Job support is a common feature of machine learning bootcamps—it helps boost the success of graduates, in turn boosting the reputation of the school. If you’re planning to pay $10,000 for a bootcamp, it should definitely have job support included.
Some schools offer better support than others, of course. Here are some of the best benefits to look out for:
1-on-1 calls with a career expert
Job strategy development
Access to support after graduation
Time commitment is a very important piece of the puzzle when it comes to choosing a bootcamp. Most bootcamps are either full-time, part-time, or flexible. However, both full-time and part-time options can include live classes that you have to attend to pass the course. For part-time options, classes are often three days a week and you can choose from daytime or evening classes.
Reputation and Reviews
Choosing the right bootcamp is generally very subjective—it all depends on your unique situation. However, there is one airtight rule: always check the reputation and reviews of the school.
This is fairly easy to do with sites like Course Report, Switch Up, and Career Karma, each with reviews of hundreds of schools. You can also search for threads on Reddit to see real people discussing the pros and cons of different courses. Also, check Youtube for video reviews.
Making the Most Out of Your Machine Learning Bootcamp in San Diego
Picking the right school is only the first step of your journey and once everything is decided, it’s on you to make the most out of your course.
Are There Any Prerequisites for a Machine Learning Bootcamp?
Unlike coding bootcamps, machine learning bootcamps are more likely to have prerequisites. This is because it’s quite an advanced field, and it’s better for students to already know some programming and some math to help them on their way.
However, some bootcamps do offer courses that require no prior experience. They’ll teach you Python from scratch and give you everything you need to study the math that’s necessary for machine learning applications.
So if you have some experience, choose a course with the prerequisites to avoid re-learning things you already know. If you have no experience at all, make sure you choose a beginner-friendly course that you’ll be able to keep up with.
What Should You Expect to Learn in a Machine Learning Bootcamp?
The three main areas any machine learning course should cover are:
Data fluency: mastering data processing, cleaning, manipulation, and analysis
Machine learning models: key machine learning algorithms and how they work
Deployment and productization: how to deploy models and use them as part of a larger project
Each of these three areas will be split into many subtopics, but this is the general flow you need to look for. You can’t be a machine learning engineer without understanding data, and you can’t manage a project efficiently without understanding machine learning architecture and platforms.
What Are the Next Steps After a Machine Learning Bootcamp?
The best thing to do after graduating is jump right into searching for a job. But while you’re applying, you can also study for a machine learning certification, like the Azure AI Engineer or IBM Machine Learning Professional certification. A hiring manager might not know about the bootcamp you enrolled in, but they’ll definitely know the names Azure and IBM. These kinds of certifications validate your skills on a global level and tell the hiring manager exactly what you’re capable of. Attaching a trustworthy name to your resume can even help viewers put more trust in the rest of your resume.
Machine Learning Job Market and Outlook in San Diego
As you might expect, there is a wealth of tech companies with offices in San Diego, including big names like Amazon, Apple, Google, IBM, Microsoft, Intel, AMD, Oracle, HP, Meta, Salesforce, Dell, Fujitsu, Uber, and Adobe. There are also machine learning companies and plenty of companies in other sectors that heavily rely upon machine learning.
Here are some companies in San Diego with current job openings:
Apple is a hardware and software developer that uses machine learning in many of its products. This job post is specifically for video processing for products like FaceTime, Screen Share, AirPlay, etc.
Resources to Find Machine Learning Jobs in San Diego
Here are some resources for finding machine learning jobs in San Diego.
Besides the obvious job boards like Indeed, check out these job boards that are specific to San Diego:
Network and LinkedIn
Remember, machine learning and data science jobs exist across all industries. You don’t need to limit yourself to tech giants like Google. Instead, use your existing network to see what kinds of machine learning jobs are available. You can also keep in touch with other graduates from your cohort and see what kinds of places they’re applying to.
Online and Slack Communities
One way to quickly expand your network is to participate in online communities. These are often filled with a mix of enthusiasts, students, and experienced workers. If you make a good impression, you could even earn referrals to companies.
Machine Learning Bootcamp FAQs
We’ve got the answers to your most frequently asked questions:
Do companies in San Diego hire machine learning bootcamp graduates?
Yes. Some bootcamp providers even have their own set of hiring partners. These are companies that have partnered with the school for recruitment services. It’s a great way for companies to get quick hires that they know are trained well enough for an entry-level position.
What jobs can you apply for after a machine learning bootcamp?
There are many role titles within machine learning, but here are some of the big ones to look out for: data scientist, natural language processing scientist, business analyst, human-centered machine learning designer, research scientist, and distributed systems engineer.
Does a machine learning bootcamp look good on a resume?
Yes, but it helps to supplement this with certifications and an impressive machine learning portfolio.