Daniel Tement

Področja izobraževanja

vodi predavanja in vaje s področij:

• poslovna analitika
• poslovna inteligenca
• umetna inteligenca
• strojno učenje
• osnove programiranja

Področja projektnega sodelovanja

Znotraj tega projekta pomagamo podjetjem na več področjih:

Skrb za zdravje

• razvoj algoritmov in modelov za optično metodo neinvazine detekcije parametrov v krvi in koži človeka (stopnja sladkorja, holesterola, bilirubina, …); pri tem uporabljamo analizo podatkov z različnimi metodami, kot so korelacijska analitika, regresija, nevronske mreže, strojno učenje,…
• pomoč na področju statistike in poslovne inteligence pri analizi in vizualizaciji podatkov na področju raziskav matičnih celic;

Kmetijstvo

• razvij algoritmov in modelov za hitro in preprosto detekcijo določenih substanc v kmetijskih pridelkih;

Pametna okolja

• pomoč pri razvoju platfrome za vzpostavitev pametne tovarne;
• razvoj poslovne inteligence in optimizacije za področje pametne logistike;

Areas of education

Leads lectures and exercises from different fields.

Business Analysis

1. The Need for Business Analysis
2. The Breadth and Depth of the Ba Role
3. Roles and Responsibilities
4. Frameworks, Tools and Techniques
5. Career Roadmap

Business Intelligence using Tableau

1. Data Preparation
2. Basic Charts
3. Advanced Charts
4. Interactivity
5. Dashboards and Story Points
6. Maps and Geospatial Visualization

Data Science using R

1. Introduction to RStudio
2. Data Import and Data Manipulation
3. Basic Data Visualization
4. Basic Statistics
5. Linear Regression
6. Basics of Deep Learning and Mashin Learning

Programming with Pyton

1. Programming tool PyCharm
2. Numbers and Expressions
3. Strings and Functions
4. Variables
5. Taking input
6. If Statements
7. Lists
8. Loops
9. Dictionaries and Tuples
10. Functions

Areas of research

Health care

• development of algorithms and models for optical noninvasive detection method for blood and human skin parameters (sugar, cholesterol, bilirubin, …); using data analysis with various methods, such as correlation analysis, regression, neural networks, machine learning, …
• statistics and business intelligence in the analysis and visualization of data in the field of stem cell research;

Agriculture

• development of  algorithms and models for quick and easy detection of certain substances in agricultural products;

Smart Environments

• development of the model and platform for the establishment of a smart factory;
• development of business intelligence and optimization in the field of smart logistics;