Data Scientist

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ATTENTION: in the academic year 2020/21 the course will not be launched – we invite you to learn about the offer of postgraduate studies Business Analyst

Objective

The objective of the studies is to introduce future Data Scientist and analysts to the complete methodology of machine learning projects: from business data models, statistics, R language to learning and deep machine learning techniques. The students will have the opportunity to work with a wide set of tools and programmes and conduct, from start to finish, machine learning experiments on their own.

What makes us different

• An attractive programme that encompasses the skills that are increasingly sought after around the world, without general or introductory subjects
• Classes conducted by experts who are also experienced lecturers – well known throughout Poland.
• All classes are held in well-equipped computer labs, and based on the most popular and the latest software: SQL Server 2018, Power BI, R, Azure ML Studio and Azure Cognitive Services.
• Interest-free instalment payments are available
• No enrolment fees
• All the lecturers were awarded the prestigious title of MVP in Artificial Intelligence or Data Platform category

Benefits

• Classes are conducted in modern laboratories at WSZiB, and based on authorised materials of experienced lecturers.
• Assessment projects that you will want to brag about on social media.
  The students receive a diploma of completion of postgraduate studies (a copy in Polish and in English).

Lecturers

• MA Eng. Marcin Szeliga – A machine learning practitioner working with SQL Server and Azure on a daily basis. Since 2006, he has continuously been awarded the title of Microsoft Most Valuable Professional, one of two Polish people holding the title of MVP in AI category. Speaker at many European conferences such as Machine Learning Prague, Data Science Summit, SQLDay, 4 Developers, SQL Nexsus and SQL Saturday. Author of books and articles on the Microsoft data platform, including the 2017 PWN bestseller “Data Science i uczenie maszynowe” (ENG: “Data Science and Machine Learning”) and “Praktyczne uczenie maszynowe” (ENG: “Practical Machine Learning”), PWN 2019.
• Grzegorz Stolecki, MA – he has been involved in multidimensional data sets, artificial intelligence and controlling since 1994. He designs and implements analytical solutions based on data warehouses dedicated primarily to medium and small businesses. He is one of the leaders of Polish SQL Server User Group Katowice. In January 2010, he was awarded the title of MVP in SQL Server category. He has spoken numerous times at conferences, including SQLDay, SQLDay Workshop, and Microsoft Technology Summit.
• MA Eng. Tomasz Libera – SQL Server specialist, trainer, SQLDay conference speaker, board member of PLSSUG – SQL Server Users Association. In April 2017, he was awarded the title of MVP in the SQL Server category.

Curriculum

Business data models

The aim of the course is to prepare future analysts, BI specialists and database programmers to develop Business Intelligence systems using Microsoft technologies.

1. Analytical data models. Designing and creating tabular models.
2. DAX as a data modelling language.

Data reporting and presentation

1. Creating Power BI reports.
2. Implementing reports in the Power BI service.

Machine learning

1. Regression models versus partition models. CRISP-DM and TDSP Methodologies. Azure AutoML Service.
2. Azure ML Studio. Classification through induction of decision trees. Classification using a support vector machine.
3. Azure ML Studio. Linear regression. Artificial neural networks
4. Azure ML Studio. Grouping, recommending and forecasting. Evaluation, quality improvement, and implementation of predictive models.
5. SQL Server Machine Learning Services. Assessing data usability. Data pre-processing, enrichment, cleansing and transformation. Data reduction and partitioning methods.
6. SQL Server Machine Learning Services. Regression and classification models. Evaluation, optimisation, and implementation of predictive models.

detailed curriculum 

Machine learning

1. Azure Cognitive Services. Image analysis. Object recognition and detection in images. Splicing networks. Azure Custom Vision service.
2. Azure Cognitive Services. Text and sound analysis. Language Understanding service.

R as an advanced data analysis language

1. Introduction to the R language. Data types and structures
2. Programming in R language. Instructions that control program execution. Input/output instructions
3. Working with data. Data science libraries. Organizing the data. Data preparation for analysis.
4. Data analysis and visualization. The ggplot2 library. Data quality assessment.

detailed curriculum

Requirements

• Foundations of T-SQL programming
• Knowledge of data warehousing and ETL processes

If you do not meet the above criteria, you are welcome to study the “SQ Server Specialist” programme

Fees

PLN 4000 or 4 equal, interest-free instalments (including PLN 100 reservation fee)

Bank account number: 61 1440 1127 0000 0000 0193 3148
On-campus sessions: Saturday – Sunday
Number of months: 10