Резултати од пребарување

Statistics for data analysis (4+1)

1. General Information

This program is designed to train staff with solid statistical knowledge with a focus on the newly recognized field of data science. The curriculum combines rigorous statistical theory with broader practical experience in applying statistical models to data work. Graduates will be in high demand. Most students are expected to be employed as statisticians, analysts and data experts within private and public institutions providing statistical consultations.

  • Name of the proposer: University "Ss. Cyril and Methodius University in Skopje, Faculty of Information Sciences and Computer Engineering - FINKI
  • Title of the study program: Second cycle academic studies in Statistics for Data Analysis
  • Scientific-research area: technical-technological / natural mathematical
  • Field: Informatics / Mathematics
  • Areas: Mathematical Statistics and Operations Research, Data Processing, Applied Mathematics and Mathematical Modeling, Programming, Artificial Intelligence, Algorithms, Information Processing .
  • The value of postgraduate studies is 60 ECTS credits.
  • Duration of studies: 2 semesters .
  • One academic year consists of two semesters lasting 30 weeks (1 semester = 15 weeks).
  • Conditions for enrollment : according to the competition announced by the university, completed undergraduate studies in information science, computer or related fields with a minimum of 240 credits.
  • First semester: 3 compulsory courses and 2 electives, one of which may be from the University list.
  • Second semester : 1 compulsory and 1 elective course and completed project - master's thesis of 18 ECTS.
  • 1 ECTS credit corresponds to 30 hours of total work engagement.
  • The number of contact hours is 4.
  • The academic title or degree obtained upon completion of the studies is Master of Information Science - Statistics in Data Analysis

                Master of Science in Informatics - Statistics for Data Analytics

 

2. Studies

Table 2: List of Postgraduate Courses in Statistics for Data Analysis

РБ CODE / Subject Semester M / E ECTS
1 SNP-Z-1 Data analysis with statistical packages IX M 6
2 SDP-Z-3 Bayesian data analysis IX M 6
3 SDP-Z-4 Data preparation and research IX M 6
4 Elective item from Table 4 IX E 6
5 Elective item from Table 4 IX E 6
6 SNP-Z-2 Regression Models X M 6
7 Elective item from Table 4 X E 6
8 Masterrska topic X M 18

 

Table 3 shows the electives from the study program Statistics for Data Analysis. In addition to these courses, the student can choose from all elective courses, defined for all study programs, from the second cycle that are serviced by the faculty. It is allowed to choose one elective course from the university list of free elective courses.

 

 

Table 3: Optional list of offered items

РБ New code /   Subject Semester ЕКТС
1 Methods of statistical locking IX 6
2 Concepts and application of big data IX 6
3 Analysis and forecasting time series IX 6
4 Advanced Algorithms IX 6
5 Modeling and fusing IX 6
6 Information Processing in Biological Systems IX 6
7 Analysis of data from related systems IX 6
8 Text Data Processing IX 6
9 Optimization methods IX 6
10 Data processing in bioinformatics IX 6
11 Network Analysis IX 6
12 Ambiental intelligence IX 6
13 Web of the Future IX 6
14 Statistical programming X 6
15 Statistical Learning X 6
16 Multidimensional statistical analysis X 6
17 Numerical methods for data science X 6
18 Statistical research skills: editing , reporting and visualization of data X 6
19 Business Analytics X 6
20 Random processes X 6
21 Big Data Modeling and Management X 6
22 Discovering knowledge in big graph data X 6
23 Open and related data X 6
24 Modern Simulations and Modeling X 6
25 Computational paradigms in the Internet of Things X 6
26 Data analysis from mobile sensors / sources X 6
27 Intelligent mobile applications X 6

 

The student can choose a subject from the list of offered elective courses from all study programs of the second cycle of studies. The list of offered electives can be found on this   link .

 

Statistics for data analysis (3+1+1)

1. General Information

This program is designed to train staff with solid statistical knowledge with a focus on the newly recognized field of data science. The curriculum combines rigorous statistical theory with broader practical experience in applying statistical models to data work. Graduates will be in high demand. Most students are expected to be employed as statisticians, analysts and data experts within private and public institutions providing statistical consultations.

  • Name of the proposer: University "Ss. Cyril and Methodius University in Skopje, Faculty of Information Sciences and Computer Engineering - FINKI
  • Title of the study program: Second cycle academic studies in Statistics for Data Analysis
  • Scientific-research area: technical-technological / natural mathematical
  • Field: Informatics / Mathematics
  • Areas: Mathematical Statistics and Operations Research, Data Processing, Applied Mathematics and Mathematical Modeling, Programming, Artificial Intelligence, Algorithms, Information Processing .
  • The value of postgraduate studies is 120 ECTS credits.
  • Duration of studies: 4 semesters .
  • One academic year consists of two semesters lasting 30 weeks (1 semester = 15 weeks).
  • Requirements for enrollment : according to the competition announced by the university, completed undergraduate studies in information science, computer or related fields with a minimum of 180 credits.
  • Introductory Layer : The introductory layer is the first two semesters in which students are offered a set of differential introductory courses. After their successful realization, the student acquires the right to continue with the second year of postgraduate studies.
  • Third semester: 3 Mandatory courses and 2 electives, one of which may be from the University list.
  • Fourth semester : 1 Mandatory course and 1 elective course, the elective course can be from the University list (only if in the first semester the courses are selected at the Faculty level) and the final project - master's thesis from 18 ECTS.
  • 1 ECTS credit corresponds to 30 hours of total work engagement.
  • The number of contact hours is 4.
  • The academic title or degree obtained upon completion of the studies is Master of Science in Information Science - Statistics for Data Analysis

                Master of Science in Informatics - Statistics for Data Analytics

 

2. Introductory layer

The first year of study is the introductory layer for students whose studies lasted less than four years, ie students who gained 180 credits from previous studies. Students must pass differential exams that will enable them to enter the basics of mathematics and computer science needed to successfully complete their studies.

Table 1: List of subjects in the first year of study

РБ CODE / Subject Semester M / E ECTS
1 Mandatory subject 1 from Table 2 VII M 6
2 Mandatory subject 2 from Table 2 VII M 6
3 Mandatory subject 3 from Table 2 VII M 6
4 Mandatory subject 4 from Table 2 VII M 6
5 Elective course 1 * VII E 6
6 Mandatory subject 5 from Table 2 VIII M 6
7 Mandatory subject 6 from Table 2 VIII M 6
8 Mandatory subject 6 from Table 2 VIII M 6
9 Elective course 5 * VIII E 6
10 Selection from the university list of free courses VIII E  

 

Elective courses can be selected from the proposed list of courses of the study program (Table 2), or from the proposed lists of courses from the introductory layer of other study programs of the Faculty of Information Sciences and Computer Engineering. The selection of courses should be made in accordance with the previous knowledge of the candidate and the necessary knowledge to continue with the postgraduate studies in statistics for data analysis. When choosing courses, the student should coordinate with the head of the study program. A free choice of subject is also allowed, which is on the university list of subjects for the first year of two-year postgraduate studies.

After the successful completion of all ten courses and 60 credits, the student with previously acquired 180 ECTS credits (or completed three-year studies) continues with the courses from the second academic year of postgraduate studies - Table 3 (III and IV semester).

  * Selection from the lists of subjects from the introductory layer of all master studies at the Faculty of Information Sciences and Computer Engineering

 

Table 2: List of recommended courses in the first year of study

РБ New code /   Subject Semester ECTS
1 F18L1W011 Discrete Mathematics VII / VIII 6
2 F18L1S013 Calculus VII 6
3 F18L2W006 Probability and statistics VII 6
4 F18L3W035 Linear Algebra and Applications VII 6
5 F18L3W008 Introduction to Data Science VII 6
6 F18L3W161 Social Networks and Media VII 6
7 F18L3W108 Internet of Things VII 6
8 F18L3W004 Databases VII 6
9 F18L3W068 Computing in the Cloud VII 6
10 F18L3S036 Machine learning VIII 6
11 F18L3S150 Data Mining VIII 6
12 F18L3S163 Statistical Modeling VIII 6
13 F18L3S157 Data warehousing and analytics VIII 6
14 F18L1S023 Business Statistics VIII 6
15 F18L3W076 Introduction to time series analysis VIII 6

 

Table 3: List of Postgraduate Courses in Statistics for Data Analysis

РБ CODE / Subject Semester M / E ECTS
1 SNP-Z-1 Data analysis with statistical packages IX M 6
2 SDP-Z-3 Bayesian data analysis IX M 6
3 SDP-Z-4 Data preparation and research IX M 6
4 Elective item from Table 4 IX E 6
5 Elective item from Table 4 IX E 6
6 SNP-Z-2 Regression Models X M 6
7 Elective item from Table 4 X E 6
8 Master Thesis X M 18

 

Table 3 lists the electives from the Statistics for Data Analysis study program. In addition to these courses, the student can choose from all elective courses, defined for all study programs, from the second cycle that are serviced by the faculty. It is allowed to choose one elective subject from the university list nand free electives.

 

 

Table 4: Optional list of offered items

РБ New code /   Subject Semester ECTS
1 Methods of statistical locking IX 6
2 Concepts and application of big data IX 6
3 Analysis and forecasting time series IX 6
4 Advanced algorithms IX 6
5 Modeling and fusing IX 6
6 Information Processing in Biological Systems IX 6
7 Analysis of data from related systems IX 6
8 Text Data Processing IX 6
9 Optimization methods IX 6
10 Data processing in bioinformatics IX 6
11 Network Analysis IX 6
12 Ambiental intelligence IX 6
13 Web of the Future IX 6
14 Statistical Programming X 6
15 Statistical Learning X 6
16 Multidimensional statistical analysis X 6
17 Numerical methods for data science X 6
18 Statistical research skills: editing , reporting and visualization of data X 6
19 Business Analytics X 6
20 Random processes X 6
21 Big Data Modeling and Management X 6
22 Discovering knowledge in big graph data X 6
23 Open and related data X 6
24 Modern Simulations and Modeling X 6
25 Computational paradigms in the Internet of Things X 6
26 Data analysis from mobile sensors / sources X 6
27 Intelligent mobile applications X 6

 

The student can choose a subject from the list of offered elective courses from all study programs of the second cycle of studies. The list of offered electives can be found on this   link .

NI4OS-Europe

Body: 

ni40s.jpg

National Initiatives for Open Science in Europe – NI4OS Europe, aims to be a core contributor to the European Open Science Cloud (EOSC) service portfolio, commit to EOSC governance and ensure inclusiveness on the European level for enabling global Open Science.

The project’s main actions include

  1. Support the development and inclusion of the national Open Science Cloud initiatives in 15 Member States and Associated Countries in the EOSC governance.
  2. Instill within the community the EOSC philosophy and FAIR principles for data Findability, Accessibility, Interoperability and Reusability.
  3. Provide technical and policy support for on-boarding of service providers into EOSC, including generic services (compute, data storage, data management), thematic services, repositories and data sets.

More details about the project at the official web site https://ni4os.eu/

The role of FCSE, UKIM in the project

FCSE, UKIM will liaise with stakeholders, collect relevant information for roadmapping, facilitate the setup of national OSC initiative in the country, and support national EOSC liaison. FCSE, UKIM will also lead the WP that will contribute to defining the set of operational best practices and develop appropriate tools that will enable harmonization and on-boarding possibilities for the service providers. It will support the on-boarding of generic and thematic services and repositories in the country to EOSC and support the horizontal platform. Additionally, it will promote FAIR and EOSC uptake in the national communities, deliver trainings, and develop specific IT service management courses and training materials. It will lead the training task and provide the project level training platform. National dissemination events will be organized by FCSE, UKIM.

 

Are you looking for a content-reach but really fun internship where you can learn, create meaningful things and work on real projects that make a difference? We mentor, we progress and we are open to ideas! Join our Internship Program:  

  • Software Engineer:

          Skopje: https://bit.ly/3xMrehK

          Bitola: https://bit.ly/3h07Etb

          Ohrid: https://bit.ly/3h45V4D

netsetera.png

0

Компанијата Loka (loka.com) објавува пракса за Data Engineers за студентите на Финки. Во текот на праксата студентите ќе се запознаат со алатки за работа со големи податоци (Big Data) и ќе се усовршат во ETL (extract, transform, load) процесите за користење на податоците во реални апликации. За таа цел ќе се користат мноштво од AWS алатки за внес на податоци со Glue, Kinesis, Elastic Map Reduce и open source алатките Spark, Beam и Airflow, чување на податоци со Redshift и S3/Parquet и визуелизација со Athena и QuickSight.
По завршување на праксата ќе знаете да дизајнирате и имплементирате системи за работа со големи податоци во полиња како machine learning, life sciences и medicine.
Заинтересираните кандидати може да се пријават на следниот email: hx@loka.com

1

Компанијата QtWinSoft од Скопје, има потреба за вработување на студенти од завршна година/и со или без работно искуство. Како компанија нудиме одлични можности за учење и брз развој на вештини за оние кои што би сакале да научат и да учествуваат во развој на C++ multiplatform Desktop/Mobile/Embedded апликации. Проектите се изработуваат со користење на cross-platform framework Qt/QML, од следниве области: vehicle dashboard and infotainment, electrical vehicle, cabin management system for airplanes, machine learning, medical applications, CRM software, 3D visualization with visualization Toolkit (VTK), Open Cascade, data encryption and security, video and audio processing, VoIP...

 

Заинтересираните кандидати може да пратат CV на следнава email адреса: qtwinsoft@gmail.com или на контaкт формата на нашата веб страна: www.qtwinsoft.com

1

Табови

Milos Jovanovik Ph.D.

Synami is a company that focuses on developing innovative software products with strong potential to lead the digital transformation and revolutionize the workflows of the world' leading global companies. Our portfolio of products is being used by over 4,500 companies, ranging from micro-companies all the way to 70% of the large Fortune 500 enterprises, and is recognized in over 172 countries across the globe.

Our team of professionals lives and breathes innovation, which when blended with a strong passion for design and development produces high-quality products.

We have a new open position for a Python developer and we are looking for a talented and ambitious software engineer who would like to work and further grow in a comfortable, respectful, supportive and collaborative environment.

 

Requirements:

· Experienced in developing Python applications, with knowledge of at least one Python web framework (such as Django or Flask)

· Familiarity with some ORM (Object Relational Mapper) libraries

· Able to integrate multiple data sources and databases into one system

· Understanding of the concurrency models of Python, and multi-process architecture

· Good understanding of server-side templating languages (Django

· Basic understanding of front-end technologies, such as JavaScript, HTML5, and CSS3

· Understanding of accessibility and security compliance

· Knowledge of user authentication and authorization between multiple systems, servers, and environments

· Understanding of fundamental design principles behind a scalable application

· Able to create relational database schemas that represent and support business processes

· Strong unit test and debugging skills

· Proficient understanding of code versioning tools (such as Git) To apply for this open position send your CV at careers@synami.com.

If you have any additional question about this open position feel free to write to us at careers@synami.com.

1

Internships are the perfect opportunity to gain professional experience and bridge the gap to your next role, and the Netcetera Spring Intership Program is now open!
Deciding on how you work is totally up to you, in our office or from home, you will get to build your skills with the support of our experts and dedicated mentor. 
 
Join our Internship Program: 

 

 

0

Metergram is excited to welcome "Powering the Future", an event dedicated to the latest trends and breakthroughs in EV charging with the support of our friends at Women in Tech® Macedonia.

No matter your background – industry expert, EV enthusiast, student, or forward-thinking professional – join us to gain valuable insights into the latest EV charging technologies and trends.

Key topics to be covered:

  • Turning Data into Insights: The Architecture Behind a Modern Data Platform with Fabric – Explore how data analytics is contributing to business intelligence and decision-making
  • EV Charging Flow in Action: Understanding the Process – A deep dive into the EV charging flow, from authorization to session completion
  • Comprehensive Technical Audit of an EV Charging Software System – A closer look at what a technical audit involves to ensure optimal performance and reliability
  • Breaking the QA Myth: It's Not Just Testing, It's Business Success – Unravel the critical role of quality assurance in EV charging solutions
  • Overview of EV Charging Protocols and the Role of OCPP – Understand the significance of communication protocols in ensuring interoperability
  • OCPI: An Overview of EV Roaming – Understand how the Open Charge Point Interface enhances interoperability
  • Beyond the Plug: The Digital Transformation of EV Charging Solutions – Discover how digital technologies are revolutionizing the EV charging landscape

Be at the forefront of EV charging innovation!

Register here: https://lnkd.in/dVgG6fWw

1