Program Overview
Vistula University's Full-Stack Data Science Program is a 16-week, 200-hour certified postgraduate program that equips technical teams with industry-specific data science skills. The program covers essential tools and algorithms used by top companies worldwide, preparing graduates for roles as Data Analysts and AI specialists. With hands-on experience, portfolio building, and expert guidance, the program provides a strong foundation for success in the current and future job markets.
Program Outline
Vistula University Full-Stack Data Science Program
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Degree Overview:
Overview:
This certified postgraduate program prepares technical teams with industry-specific skills in data science. Addressing the growing demand for skilled data scientists, the program equips you with essential skills and tools used by top companies worldwide.
Objectives:
- Identify, apply, and compare various AI algorithms on data.
- Gain familiarity with leading data science tools, libraries, and their applications.
- Practice industry-preferred Machine Learning packages through hands-on experience.
- Provide companies with well-trained project team members.
- Effectively communicate your findings to a general audience.
Description:
With courses in Data Analytics, Python, Data Visualization,Applied Machine Learning, and Deep Learning, this program prepares you for the current and future job markets. Additionally, the program offers:
- Portfolio building with real-life projects
- Data Cleaning and Data Wrangling
- Machine Learning Basics (Supervised/Unsupervised Learning)
- Deep Learning using Keras and Tensor Flow
- NumPy, Pandas, Seaborn
- Seminars with expert data scientists
- Practicing job interviews
- Career Coaching
Careers:
Postgraduate program graduates hold the potential role of:
- Data Analysts
- AI specialists
Tuition fee: 1900 Euros Diploma fee: 50 Euros
Full-Stack Data Science - Entry Requirements and Language Proficiency:
Entry Requirements:
- Academic Qualifications:
- Bachelor's degree from an accredited university in any field.
- Minimum GPA of 3.0 on a 4.0 scale.
- Completion of prerequisite courses in mathematics, statistics, and programming. Specific courses may vary depending on the applicant's background.
- Professional Experience:
- Prior experience in data analysis, machine learning, or related fields is preferred but not required.
- Experience with data visualization tools and libraries is beneficial.
Language Proficiency Requirements:
- English:
- TOEFL score of 80 or higher, or
- IELTS score of 6.5 or higher, or
- PTE Academic score of 58 or higher, or
- Completion of a recognized English language proficiency program.
Additional Requirements:
- Personal statement outlining the applicant's interest in and qualifications for the program.
- Two letters of recommendation from academic or professional references.
- Resume or CV highlighting relevant experience and skills.
Note:
The specific entry requirements and language proficiency requirements may vary depending on the applicant's individual circumstances. It is recommended that prospective students consult the program website or contact the program directly for the most up-to-date information.