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DSTI Learning Methodologies

DSTI takes enormous pride in our unique learning methodology that offers a concept-focused curriculum, industry-driven courses, personalised support, hands-on projects and learning infrastructure.

Mastering Science, Technology, Engineering, and Mathematics (STEM) Foundations for AI: Beyond Just Learning

Have you ever wondered about the engineering marvels behind your daily commute, whether it’s by train, plane, or car, or the meticulous design of the bridges and buildings you encounter? Imagine if the engineers behind these feats had only a few weeks or months of training. Would you still trust these structures?

At Data ScienceTech Institute, we equate disciplines like computer engineering, data science, artificial intelligence, and cybersecurity with other noble scientific and engineering fields. These areas are integral parts of STEM – Science, Technology, Engineering, and Mathematics – disciplines known for their complexity and significance.

Our comprehensive curricula, at Bachelor’s and Masters’ level, champion a bottom-up approach, focusing on a lengthier, well-coordinated education in applied sciences and the fine arts of engineering. This method is crucial for instilling sustainable foundational skills in our students and graduates. While programming languages and software trends may fluctuate, the principles of algorithmics, engineering mathematics, probability, and statistics remain evergreen.

We often receive heartening feedback from our alumni, who find themselves revisiting DSTI’s foundational classes when faced with new challenges. This testament to the balance of our programmes’ curricula, which merges demanding foundational courses with cutting-edge technological applications, underscores the success of our graduates’ careers.

Embark on an educational journey with Data ScienceTech Institute, where the rigorous pursuit of STEM knowledge ensures a fulfilling and enduring career path.

Attend Industry-driven courses

The tech industry is the driving force behind today’s innovation, and it is happening rapidly. As a result, the skills needed to succeed in technology companies are changing. To ensure that students are prepared for this changing landscape, DSTI’s scientific committee comprises individuals who are at the forefront of these advancements. They create relevant curricula to ensure student success.

DSTI offers industry-relevant programmes in Data and AI

Applied Bachelor in Data & Cloud Engineering

Applied MSc in Cyber Security

Applied MSc in Data Analytics

Applied MSc in Data Engineering for AI

Applied MSc in Data Science & AI

ENSAM & DSTI Joint Programme in Digital Industry and AI

Get personalised support

At DSTI, we value open communication between students and instructors. So, we offer support sessions after each course and before exams. During these sessions, students can ask questions about course material or any challenges they may have encountered while studying on their own. This helps to boost their confidence when it comes to taking exams, completing projects, and participating in internships.

Build practical coding skills

To enhance employability, only conceptual understanding is not sufficient. Students need to have practical coding skills. So, DSTI places great emphasis on providing students with various opportunities to work on hands-on projects, attain certifications, and engage with the industry. By doing so, our graduates are well-equipped to take on professional challenges in their chosen fields.

Leverage self-learning infrastructure

Each student has access to our online learning platform which provides them with a range of resources. These include schedules, live lectures that are held online, as well as notes. Additionally, students can replay recordings of past lectures whenever they need to. Finally, students take their exams on this platform and can also submit their assignments and projects using it.

Explore careers in Data and AI 10 July 2024.

On our Open Days, know more about

  • On-Campus and Online Modes
  • Interactive Sessions on careers in data and AI.
  • Socialise with current and future students.
  • Know the Admissions Process.