Project Future 10: Business Intelligence & Data Engineering
Description
The specialized training Business Intelligence & Data Engineering powered by Code.Hub, in exclusive collaboration with Athens Tech College, invites you to claim a paid full-time position in the business world.
Business Intelligence & Data Engineering is an intensive program lasting 100 hours in 8 weeks, with theoretical and predominantly hands-on training, focusing on the use of top tools used in the field of data, modern technologies and techniques, such as Relational Databases and Big Data, and data processing and analysis languages, such as SQL and DAX, both on-premises and in the cloud.
In addition, the participants of the program will delve into the topics of Data & Data Management Systems, Data Warehouses, Data Integration, Data Analysis, Data Visualization. At the end of the training, they will be able to create and present the results of their analyses and support the decision-making process, using modern visualization tools such as Power BI.
This training will result in the preparation of professionals specialized in the field of corporate data management, who can use technologies, techniques and tools that make them competitive in the technology and business market in the fields of Data Engineering and Business Intelligence.
Duration & Schedule
This specific program lasts 8 calendar weeks and consists of 100 hours of lectures and hands-on exercises on real case studies and projects via virtual classroom environment* and online collaboration platforms.
Start Date: 07 November 2023
End Date: 12 January 2024
Detailed Schedule (*The Schedule is subject to adjustments)
| Introduction Day Tuesday 07, November 2023 |
Approximate (17.30-18.00) |
| Week 1 07, 09, 10 |
Weekdays – (18.00 – 21.15) |
| Week 2 14, 16, 17 |
Weekdays – (18.00 – 21.15) |
| Week 3 21, 23, 24 |
Weekdays – (18.00 – 21.15) |
| Week 4 28, 30, (Dec.) 01 |
Weekdays – (18.00 – 21.15) |
| Week 5 05, 07, 08 |
Weekdays – (18.00 – 21.15) |
| Week 6 12, 14, 15 |
Weekdays – (18.00 – 21.15) |
| Week 7 19, 21, 22 |
Weekdays – (18.00 – 21.15) |
| Week 8 (Jan.) 08, 09, 11, 12 |
Weekdays – (18.00 – 21.15) |
| Presentations Day Friday 12, January 2024 |
Approximate (18.00 – 21.15) |
Key Objectives – Curriculum
This program will present, explore and cover with extended hands-on sessions & real-life case studies the following areas:
- Software Engineering Aspects
- Data, Data Stores & Big Data
- Business Intelligence Ecosystem
- Data Warehouses
- Data Integration with SQL & SSIS
- Data Integration on Cloud Platforms
- Data Analysis & Business Analytics
- Data Transformation
- Data Visualization & Reporting
Conditions for participation:
Graduates of Greek or foreign schools of higher education (AEI / TEI / College), one of the following academic directions:
- Computer Science, Computer Engineering, Programming
- Electrical Engineering and Electronic Engineering
- Mathematics
- Statistics
- Physics
- Business
- Finance
Additional Conditions:
Up to 29 years old, as the program is aimed at graduates at the beginning of their careers.
Zero or limited work experience:
Work experience from 0 to 3 years full time, upon completion of studies.
Extracurricular activities:
Active involvement in extracurricular activities (eg volunteering, sports, entrepreneurship, art and any other non-academic activity).
Purpose
The purpose of the training Business Intelligence & Data Engineering powered by Code.Hub is to prepare professionals specialized in the field of corporate data management and analysis, who have the knowledge of the modern technologies, techniques and tools and make them competitive in the technology and business market and be able to claim positions in the fields of Data Engineering and Business Intelligence. The role of Data Engineers is extremely important for the effective generation and use of data and information. The profession is viewed as one of the fastest growing professions in recent years, with cutting-edge companies constantly hiring Data Engineers to improve their operations and competitiveness.
