Located in Silicon Valley, Magnimind Academy offers two courses of study: full-stack data science and machine learning. Classes are geared to students with a science and computer background seeking to make a career change. Programs include extensive mentorship opportunities and ample job support.
A newcomer to the field of tech bootcamps, Magnimind Academy has been offering classes since 2020 and has been employing its current mentorship model since 2021. The school was started by Stanford University scientists who wished to allow scientists in other fields to retool themselves for the kinds of tech careers that might stand them in better stead in today’s job market and job markets going forward.
What began as a series of informal meet-ups eventually grew into Magnimind Academy. The school targets students with backgrounds in science and a better-than-basic handle on the principles of programming and statistics. However, Magnimind offers “mini bootcamps” (many of them free of charge) designed to prepare non-scientists for admission to the school’s bootcamp programs.
Magnimindl’s pedagogy relies heavily on 1-to-1 mentoring and multi-week projects that employ real-life datasets, the better to get students to understand real-life situations, develop their portfolios and assume in-field roles after graduation. Although a new entrant, Magnimind’s instructors (some of them PhDs, others employed in key Silicon Valley firms) have more than ten years’ experience teaching and mentoring students. The school is committed to the idea of reshaping its students’ futures and opening them to new and remunerative possibilities.
Magnimind Academy is located in Palo Alto, California, in the heart of Silicon Valley. Palo Alto is home to Stanford University, where the school’s originators are based. It sits very much in the thick of the centers for technological innovation for which Silicon Valley is internationally renowned.
Magnimind Academy has two courses of instruction: Full Stack Data Science and a Machine Learning Project/Mentorship Bootcamp. The former program is designed to take people with a scientific background (or on-the-job experience coding) and train them to assume roles in the field of data science. The Machine Learning Project is intended for intermediate-to-advanced students who know their way around machine learning algorithms and wish to develop their skills further by working 1-to-1 with experienced mentors. Data from actual Silicon Valley companies (such as Twitter) is used in the projects that constitute the bootcamp curricula.
You can see how Mangimind Academy’s bootcamps compare to those offered by other providers by consulting data science bootcamps and machine learning bootcamps pages of Noble Desktop’s Classes Near Me tool.
In addition, Magnimind Academy teaches several mini-bootcamps. These classes run on consecutive weekends and teach basic skills such as Data Science with Python or more specialized topics such as NLP (Natural Language Processing) for Non-Coders. The remedial classes are offered free to prepare students for Magnimind’s actual bootcamps.
Magnimind Academy’s Full Stack Data Science Bootcamp is a 15-week part-time program designed for students with a computing background to retool themselves to begin a data science career. Live instruction is offered for five hours per week; students are expected to spend 10-15 further hours per week studying, completing assignments, and, as the program progresses, participating in a team project based on real-life datasets with the help of an assigned mentor. The curriculum begins with the mathematical bases of data science, Python for data science programming, and SQL to query datasets. The curriculum progresses to encompass data preprocessing, machine learning, Natural Language Processing (NLP), frameworks such as NLTK and TextBlob, and, ultimately, the use of the Cloud and the analysis of Big Data.
The Machine Learning Project/Mentorship Bootcamp is run along different lines. Here, the entire curriculum is built around real-life data projects in four-week modules that are completed in teams under the supervision of a mentor. (The mentor changes from module to module, meaning that students have the opportunity to work with three different mentors in the course of the program.) The first module focuses on an NLP project using real-life X (formerly known as Twitter) data. The second is a distributed machine learning project. After that, the bootcamp culminates in a deep learning project that employs a convolutional neural network to create a system to enable computers to translate American Sign Language (ASL) into English text.
Classes at Magnimind can be taken either in person at the Palo Alto campus or fully live and online. The team of instructors and mentors is drawn both from local industry and academe. Office hours are arranged to allow for live video chats during which students may ask questions and benefit from their mentors’ input.
Given the intermediate-to-advanced nature of its bootcamps, Magnimind Academy’s admissions process is highly selective. The prerequisites for the data science program include six months’ coding experience and some understanding of probability and basic statistics concepts. The mentorship program requires what the school calls a “decent knowledge” of machine learning and its algorithms. The admissions process is also designed to ascertain whether candidates will be able to devote the time and energy the bootcamps require. Only 50% of applicants are accepted; those who aren’t are referred to the remedial mini-bootcamps and are then invited to reapply.
Magnimind advertises “the best quality education at the best prices.” The 15-week programs are priced at $2500, with a $400 early registration discount available until six weeks before the start of the class. A deferred tuition agreement is also available, through which payments are made only once the student has obtained employment following the completion of the bootcamp. However, the total cost of financing raises the cost of either bootcamp to $6000.
Those mini-bootcamps that aren’t provided free of charge are priced at $300 each.
Magnimind Academy places great stress (indeed, its entire emphasis) upon placing graduates advantageously in in-field jobs. To that end, an extensive career services component is included in its bootcamps. Mentoring plays an essential part in both bootcamp programs as well. Also included in the price of both bootcamps are practice interviews, career coaching, and resume support. The last two weeks of either bootcamp are devoted largely to career coaching and readying students for the job market.
According to Magnimind Academy’s figures, 85% of their graduates found jobs within six months of graduating. Of those, 78% were placed in roles of Data Scientist, Data Analyst, or Data Engineer. Some 65% of graduates who received offers received them for more than $60,000 per annum.
Magnimind Academy’s figures further state that graduates of the Full Stack Data Science program obtained increases in salary of $26,000 compared to what they were making before they began the program. Graduates of the machine learning program improved their salaries even more, by $27,000 on average.
Student reviews on bootcamp rating websites are almost uniformly positive, although most reviews are for the mini-bootcamps rather than the full 15-week programs. Students mentioned, “this is a great bootcamp and I learned an enormous amount of information” and called it “simply the best,” although one review noted that “the teacher covered too many topics in two days.”
Regarding the sparser reviews of the full-term programs, one review of the machine learning bootcamp mentioned “easy to understand, engaging learning methods” and “I can’t really think of a strong con.” A further student rated it “one of the best in the Bay.”
Learn more at magnimindacademy.com
The Full Stack Data Science Program is a 15-week bootcamp for students with a coding background. The program begins by teaching the mathematical foundations of data science and basic Python and takes students through to such topics as machine learning, NLP, cloud computing, and Big Data.
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Data science is one of the fastest-growing career fields, with competitive salaries and nearly endless opportunities for specialization. Data science uses machine learning algorithms, statistics and other analytic tools to understand data.