TripleTen Externships: How Data Science Students Helped Shape Cuetessa's Music App

For TripleTen students, externships serve as a crucial bridge between theoretical learning and professional practice. These immersive, short-term projects allow students to tackle genuine business challenges, apply their technical skills in real-world settings, and build professional portfolios before graduation, all while collaborating on a project with measurable business impact.

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For some recent TripleTen data science students, this experience came to life through a collaborative project with Cuetessa, the startup behind Smoothi — a cutting-edge music curation app. The partnership showcased how bridging education and industry can create beneficial outcomes for both students and businesses in tech.

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Here’s how it worked:

The project: Enhance music classification for personalized experiences

Cuetessa entered the music technology scene with a clear mission: to enhance music curation and create unique audio experiences. Their flagship product, Smoothi, allows users to customize their music experience based on mood and activity preferences, delivering seamless transitions between songs.

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Cuetessa recognized a common pain point among a subset of music fans: the jarring silence or awkward gaps between songs on traditional streaming platforms. Much like how a DJ crossfades tracks at an event, Cuetessa realized some listeners prefer seamless transitions depending on their situation — whether hosting a party, working out, or simply enjoying their favorite type of music (for example, techno or lo-fi music playlists where smooth transitions enhance the listening experience and mood).  

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“Smoothi changes how people experience music through data science,” explained the Cuetessa team. “With each song seamlessly ‘blended’ into the next, your music can match your vibe and you never miss a beat.”

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However, the TripleTen externship project addressed a different challenge at the heart of Cuetessa's business: understanding what makes songs evoke different emotional responses. “Some songs make you want to cry and some songs make you want to smile. Some songs make you want to dance and some songs help calm your nerves,” the Cuetessa team noted. “We wanted to know what features in the music actually make these differences.”

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With this question as their starting point, TripleTen students were tasked with developing methods for music classification such as energy levels and emotional responses. These classifications would ultimately help identify commonalities between songs and create smoother transitions for personalized listening experiences — a perfect blend of technical challenge and creative exploration that represents the real-world problems Cuetessa tackles daily.

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The company chose to partner with TripleTen based on previous positive experiences, as its team saw TripleTen’s bootcamps as “an excellent way to dive headfirst into the rapidly evolving worlds of software engineering and data science.” “Cuetessa worked with TripleTen in the past and expressed how impressed they were by the quality of our mentors_{At TripleTen, Learning Online Doesn’t Mean Learning Alone}, the creativity of our students, and the value of our externships,” said Marcella Mendoza Martinez, TripleTen's Data Science Externships Lead Mentor.

The process: Fine-tune music with data insights

Working in teams with regular guidance from mentors, TripleTen students tackled the music classification challenge through a structured yet collaborative approach. Weekly stand-up meetings gave students opportunities to present their progress and receive feedback, mimicking the agile environment common in tech companies.

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One significant challenge emerged early in the project: finding appropriate datasets for building machine learning models. “There are limited audio music public datasets out there because of copyright infringement issues,” explained Marcella. This constraint forced students to think creatively, eventually identifying several research-oriented datasets that were publicly available and suitable for their analysis.

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“In a short amount of time, impressive test beds in the form of code repositories were developed and became the final deliverables,” Marcella shares, highlighting how students transformed theoretical knowledge into practical solutions that could be implemented and tested.

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The technical implementation required students to apply a range of data science skills_{The Top Data Science Skills for 2025} — from audio feature extraction and preprocessing to machine learning model development and evaluation. Students had to understand both the mathematical properties of audio signals and the subjective nature of emotional responses to music, bridging technical expertise with human experience.

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Throughout the process, students gained important expertise_{Want to Really Learn Tech? Get Hands-On Experience} in problem-solving under real-world constraints. They learned to navigate ambiguity, make data-informed decisions, and communicate their findings effectively — skills that extend far beyond the technical aspects of data science.

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 “The developed methods were often excellent proof-of-concepts with a lot of potential,” Marcella reported. “The final presentations and discussions also created a lot of ideas about possible future directions.”

The impact: Harmonize education with innovation

The externship results struck a perfect chord. “These externships allowed the students to get hands-on, applying frontier computer science methods to real product applications,” Marcella said. “The program also mimicked an industry environment as collaboration with teammates, mentors, and the ‘customer’ is essential to deliver the ‘product.’”

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For Cuetessa, the project revealed fresh perspectives on music classification and curation. “We loved seeing the varied ways different people think about music, a medium that has a universal appeal,” explained the Cuetessa team. “There were many insightful approaches explored by the students that we hadn’t fully appreciated at the start of the project.”

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The externship contributed to Cuetessa's understanding of how technology can enhance music experiences, potentially influencing future product development. It also exemplified how fresh talent can bring innovative thinking to established challenges.

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The impact extended beyond the immediate project deliverables, as well, creating career pathways for participants. “One past TripleTen student is now a Cuetessa software engineer!” Marcella shared, a result that directly demonstrates how externships can lead to employment opportunities when students show exceptional skills and cultural fit.

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For students, the experience provided an invaluable portfolio addition — concrete evidence of their ability to apply data science concepts to business challenges. The project offered them insights into music technology applications while building transferable skills in collaboration, project management, and technical implementation.

Discover your externship opportunity

The successful collaboration between TripleTen and Cuetessa illustrates the transformative potential of externships in tech education. Our externship programs provide the perfect bridge between learning and professional practice, no matter if you’re interested in applying data science to a creative industry like music or wanting to use your skills in different area.

Ready to transform your technical skills into real-world impact? Check out our guide_{Externships: Your Ultimate Guide} to discover how you can gain hands-on experience through externships while making meaningful contributions to innovative companies.