Data Analytics Professional Certification Course
Program Overview
Why study this programme?
Data analytics is becoming increasingly popular among organisations to help make crucial decisions across various business functions.
If you want to get into data analytics, this course provides the foundation you need, from theory to practice. It is suitable for beginners and serves as the starting point for playing with data. By the end of this programme, you will be able to evaluate the best analytical approach for solving your business problem/s and gain an understanding of the best ways to leverage data for better outcomes.
Get ready to take your career to the next level, expand your knowledge, and embrace new challenges. Professional certificate programmes are the perfect choice, offering you the opportunity to drive real business impact.
Who is this programme for?
This programme is developed for professionals who aspire to manage an organisation and make important business decisions backed by data. In specific, the programme will be most beneficial to the following individuals:
- Professionals seeking career advancement;
- Business analysts;
- Managers and executives;
- Entrepreneurs and small business owners;
- Anyone interested in and passionate about data analytics.
Key programme details
- Delivery: Hybrid (two on-campus sessions + self-study via Canvas)
- Duration: 4 weeks
- Intakes: May, July, September, and November
- Degree awarded by: Berlin School of Business and Innovation
- Fees: BSBI students on academic degree programmes: Free* / Alumni: €625 / Non-BSBI students: €1,250
Students are eligible to attend two certificate programmes free of charge. However, if a student wishes to enrol in more than two programmes, a fee of €625 will be required for each extra programme.
This programme includes:
- Two sessions, each four hours, conducted through synchronous learning
- 42 hours of asynchronous learning via BSBI’s Educational Platform
- Final test at the end of the programme
What skills will you gain?
- Understanding the importance of data
- Statistical foundations
- Data visualisation skills
- Introduction to programming
How will you learn?
- Live learning from an expert faculty
- Learning from an industry expert
- Committed support team
- High-tech learning platform
- Forum discussion for peer-to-peer learning
Program Outline
Degree Overview:
Data Analytics Professional Certification Course at BSBI:
This course equips students with the essential knowledge and skills to succeed in the data-driven world. It provides a thorough foundation in data analytics, covering crucial areas like the significance of data in decision-making, statistical foundations, data visualization techniques, introduction to programming, and preparation for advanced topics.
Objectives:
- Equip students with in-demand data analytics skills.
- Provide a solid understanding of data analysis and interpretation. It is a well-structured program with five days of dedicated synchronous classes and opportunities for peer learning through forum discussions. The course also offers high-tech learning platform, committed support, dedicated faculty, flexible learning options, and integrated assignments to ensure a holistic learning experience.
- Statistical foundations
- Data visualization skills
- Introduction to programming
- Advanced data analysis and career path
- Hands-on training with Python
Structure:
The program is structured around five days, offering a comprehensive learning experience with dedicated synchronous classes covering the following topics:
Day 1:
Introduction to Data Analytics and Basics
Day 2:
Statistical Foundations and Data Visualisation
Day 3:
Intermediate Data Analysis and Visualisation
Day 4:
Hands-on Data Analysis with Python
Day 5:
Advanced Data Analysis and Career Path
Modules:
- Introduction to Data Analytics and Basic
- Statistical Foundations and Data Visualization
- Python Programming for Data Analytics
- Machine Learning and Data Engineering
- Business Intelligence and Data Analytics Applications
Course Schedule:
The program offers five days of dedicated synchronous classes held throughout the day.
- Day 1, 2 and 5: 10 am - 2 pm CET
Assessment:
Assessment Methods:
The program uses various assessment methods:
- Assignments: Individual assignments are integrated throughout the course with a focus on application of acquired knowledge and techniques.
- Project and Presentation Skills: Students complete a project and create presentations to demonstrate and apply their learning.
- Discussion and Participation: Active participation in forum discussions is encouraged and contributes to the final assessment.
- Attendance: Regular attendance to live classes is mandatory and factored into the overall assessment.
Assessment Criteria:
The final assessment is based on various components:
- Project and Presentation Skills: 60 marks
- Discussion and Participation: 20 marks
- Attendance: 20 marks
Teaching:
Teaching Methods:
The program employs interactive teaching methods including live lectures, discussion forums, breakout rooms, practical exercises, and project-based learning experiences.
Faculty:
The teaching faculty comprises experienced data analytics experts from academic and professional backgrounds.
Unique Approaches:
The program offers several unique features for enhanced learning, including:
- A high-tech learning platform offering a convenient and accessible platform.
- A focus on technical and practical data analysis skills for immediate application.
Careers:
Career Opportunities:
Upon completion, students will be equipped to pursue various careers in data-driven fields, such as:
- Data Analyst
- Business Intelligence Analyst
- Data Scientist
- Business Analytics Manager
- Marketing Analyst
- Statistician
- Research Analyst
Career Outcomes:
- The program welcomes professionals from various backgrounds and experience levels, including beginners and experienced analysts.
- The program syllabus is updated regularmente to reflect the evolving field of data analysis.
- Students gain access to resources for further learning and career development in data analytics.
