Project Future 11: Business Intelligence & Machine Learning
Description
The specialized training in Business Intelligence & Machine Learning 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 & Machine Learning is an intensive program lasting 100 hours, with theoretical and hands-on training focusing on top modern tools, technologies, and techniques used in the field of data, such as Relational Databases, Machine Learning, Analytics, and Big Data, as well as modern data processing and analysis languages like SQL, Python, and DAX, both on-premises and on the Cloud.
The participants of the program will delve into the topics of Data & Data Management Systems, Data Integration, Machine Learning, Data Mining, Data Analysis and Data Visualization. At the end of the training, they will be able to create and present the results of their analyses to support the decision-making process, using modern analysis techniques such as Machine Learning with Python libraries and utilizing modern visualization tools like Power BI.
Purpose
The purpose of the training Business Intelligence & Machine Learning powered by Code.Hub is to prepare professionals specialized in the field of corporate data management and analysis, who have the knowledge of technologies, techniques, and tools that will make them competitive in the job market and capable of pursuing job positions in the areas of Business Intelligence (BI), Data Integration/ETL Development, Data Analysis, Data Visualization, Data Science, Machine Learning (ML), Artificial Intelligence, as well as in relevant Consulting positions.
Duration & Schedule
This 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: 26 November 2024
End Date: 28 January 2025
Detailed Schedule (*subject to adjustments):
| Intro Day: November 26 |
Intro – (17.30-21.15) |
| Week 1 28, 29 |
Weekdays – (18.00 – 21.15) |
| Week 2 December 3, 5, 6 |
Weekdays – (18.00 – 21.15) |
| Week 3 9, 10, 12, 13 |
Weekdays – (18.00 – 21.15) |
| Week 4 16, 17, 19, 20 |
Weekdays – (18.00 – 21.15) |
| Holiday Break From 21 Dec 2024 until 6 Jan 2025 |
no sessions |
| Week 5 (2025) January 7, 9, 10 |
Weekdays – (18.00 – 21.15) |
| Week 6 14, 16, 17 |
Weekdays – (18.00 – 21.15) |
| Week 7 21, 23, 24 |
Weekdays – (18.00 – 21.15) |
| Week 8 27 |
Weekdays – (18.00 – 21.15) |
| Presentations Day: January 28 |
Presentations (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:
- Overview of Business Intelligence Ecosystem & Business Reality
- Data & Data Management Systems
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- Structured Query Language (SQL)
- OLTP & OLAP Systems
- Data Warehouses & Data Marts
- Microsoft SQL Server
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- Big Data Ecosystem & Key Technologies
- Data Integration
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- Architecture: Principles & Patterns
- ETL Processes
- SQL Server Integration Services (SSIS)
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- Data Analysis & Visualization
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- Data Analysis with Python (NumPy , SciPy, Pandas)
- Data Visualization & Dashboards
- Business Analytics (Descriptive, Predictive, Prescriptive)
- Power BI
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- Data Mining & Machine Learning
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- Classification, Regression & Clustering
- Supervised Learning
- Unsupervised Learning
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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 (e.g. volunteering, sports, entrepreneurship, art and any other non-academic activity).
