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The University of Buckingham

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Buckinghamshire

United Kingdom

Embarking on a transformative journey through the MSc in Applied Data Science program at The University of Buckingham positions students at the forefront of the rapidly evolving field of data analytics. This comprehensive program is designed to equip students with essential skills in data mining, statistical analysis, and machine learning, preparing them for a successful career in a data-driven world. As the demand for skilled data scientists continues to surge, this master's program is crafted to provide the rigorous training needed to excel in various sectors such as healthcare, finance, and information technology.

The curriculum for the MSc in Applied Data Science encompasses a rich blend of theoretical foundations and practical applications. Key modules include Data Mining and Analytics, where students delve into advanced techniques for extracting meaningful insights from vast datasets, and Machine Learning, focusing on algorithms that enable predictive modeling. Students also engage in courses like Big Data Technologies and Statistical Methods for Data Science, which are critical for understanding and manipulating large-scale datasets. This well-rounded curriculum ensures that graduates possess the knowledge and technical skills required to meet industry standards.

At the heart of the program is an experienced faculty known for their expertise in data science and analytics. Faculty members not only have extensive academic backgrounds but also bring real-world experience and contemporary research into the classroom. Their teaching methodology emphasizes interactive learning, encouraging students to engage in hands-on projects that mirror the challenges faced in the industry. This approach fosters an environment where students can apply theoretical knowledge to real-world situations, reinforcing their learning and enhancing their problem-solving abilities.

Research opportunities abound for students enrolled in the MSc in Applied Data Science. The University boasts state-of-the-art facilities and laboratories equipped with the latest technologies to facilitate groundbreaking research. Students have access to resources that empower them to undertake innovative projects, collaborate with faculty, and even contribute to academic publications. This emphasis on research not only enhances the learning experience but also prepares students to take on leadership roles in their future careers.

Moreover, The University of Buckingham has established strong connections with various industries, providing students with valuable networking opportunities. The program includes a robust internship component, allowing students to gain practical experience and apply their skills in real-world settings before graduation. This exposure helps students cultivate professional relationships and enhances their employability upon completion of the program.

The career pathways available to graduates of the MSc in Applied Data Science are diverse and promising. With the growing influence of data across industries, graduates can pursue roles such as Data Analyst, Data Scientist, and Machine Learning Engineer, to name a few. The high employability rate of graduates from this program speaks volumes about the quality of education and training received. Alumni have successfully transitioned into reputable organizations and often share their success stories, highlighting how the program has significantly impacted their professional journeys.

Unique features of the MSc in Applied Data Science at The University of Buckingham include its focus on Genetic Data Analytics, a niche area that blends data science with genetic research. This specialization offers students a unique perspective and an opportunity to work at the intersection of technology and biology, making them highly sought after in specialized fields such as biomedical research and personalized medicine. The program also emphasizes ethical considerations in data usage, preparing students to navigate the complexities of data privacy and security in their future careers.

In terms of admissions, prospective students should be aware of specific requirements. A bachelor's degree in a related field is typically expected, and all applicants must demonstrate proficiency in English through standardized tests such as IELTS (minimum score of 6.5), PTE (minimum score of 59), or TOEFL (minimum score of 79). The application deadline for this program is November 24th, 2023, ensuring prospective students have ample time to prepare their applications and secure their spots in this prestigious master's program.

If you’re considering a future in data science, the MSc in Applied Data Science at The University of Buckingham is an excellent choice. With its comprehensive curriculum, expert faculty, extensive research opportunities, and strong industry connections, this program prepares students for success in a data-driven world.

Why Study Applied Data Science at The University of Buckingham

  • A popular choice for international students with a diverse community, promoting cultural exchange and collaboration.
  • Learn from renowned faculty members who are leaders in the field and have practical experience, enhancing the academic experience.
  • Access to high-end labs and facilities that support innovative research and offer hands-on learning opportunities.
  • Excellent placement programs that connect students with leading companies, ensuring a seamless transition from education to employment.
  • A strong focus on ethical data usage, preparing graduates to tackle the challenges posed by data privacy and security in their careers.
  • Unique specialization in Genetic Data Analytics, opening pathways to careers in biotechnology and healthcare analytics.
intake

Duration

12 Months

Class Profile

Diversity

North America:

5%

Africa:

2%

UK:

65%

Europe:

15%

Others:

1%

Asia:

10%

South America:

2%

Eligibility Criteria

English Proficiency Tests

  • IELTS

    6.5

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  • PTE

    59

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  • TOEFL

    79

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Application Requirements

Here's everything you need to know to ensure a complete and competitive application—covering the key documents and criteria for a successful submission.

      Application Deadlines

      Standard Deadline
      SpringNov 24, 2023

      FAQs

      • Prospective students should be aware of the following admissions requirements:

        • A bachelor's degree in a related field is typically expected.
        • All applicants must demonstrate proficiency in English through standardized tests such as:
          • IELTS (minimum score of 6.5)
          • PTE (minimum score of 59)
          • TOEFL (minimum score of 79)

        The application deadline for this program is November 24th, 2023, giving prospective students ample time to prepare their applications.

      • The curriculum encompasses a rich blend of theoretical foundations and practical applications. Key modules include:

        • Data Mining and Analytics: Advanced techniques for extracting meaningful insights from large datasets.
        • Machine Learning: Focus on algorithms that enable predictive modeling.
        • Big Data Technologies: Understanding and manipulating large-scale datasets.
        • Statistical Methods for Data Science: Essential statistical techniques for data analysis.

        This well-rounded curriculum ensures that graduates possess the necessary knowledge and technical skills to meet industry standards.

      • The program emphasizes interactive learning, where students engage in hands-on projects that reflect real-world industry challenges. Faculty members bring a mix of extensive academic backgrounds and real-world experience, which enhances the learning environment. This approach allows students to apply theoretical knowledge to practical situations, enhancing their problem-solving abilities.

      • Graduates of the MSc in Applied Data Science can pursue diverse and promising career pathways, including roles such as:

        • Data Analyst
        • Data Scientist
        • Machine Learning Engineer

        The high employability rate of graduates from this program indicates the quality of education and training received, with many alumni transitioning into reputable organizations and sharing their success stories.

      • Unique features of the program include:

        • Focus on Genetic Data Analytics, blending data science with genetic research.
        • Emphasis on ethical considerations in data usage, preparing students to navigate data privacy and security challenges.

        This specialization provides students with a unique perspective and opportunities in specialized fields such as biomedical research and personalized medicine.

      • The University boasts state-of-the-art facilities and laboratories equipped with the latest technologies, facilitating groundbreaking research. Students have access to resources that empower them to undertake innovative projects, collaborate with faculty, and contribute to academic publications. This strong emphasis on research enhances the learning experience and prepares students for leadership roles in their future careers.

      • The University of Buckingham has established strong connections with various industries, providing students with valuable networking opportunities. The program includes a robust internship component, allowing students to gain practical experience and apply their skills in real-world settings before graduation. This exposure helps students cultivate professional relationships and enhances their employability upon completion of the program.

      • Students have access to high-end labs and facilities that support innovative research and offer hands-on learning opportunities. The state-of-the-art facilities are equipped with the latest technologies, ensuring that students can engage in meaningful research and practical applications relevant to their studies.

      • The University of Buckingham is a popular choice for international students due to its diverse community that promotes cultural exchange and collaboration. Additionally, students learn from renowned faculty members who are leaders in the field, enhancing their academic experience and providing a global perspective on data science.

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