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Ivan Zvonimir Horvat
Zagreb, Croatia
Started as a web developer in 2012, with strong focus on backend (LAMP stack) and occasionally frontend, being flexible to complete various tasks for different companies. Since 2017 I've switched my career into data integrator and gain my path into system development with continuous will to learn trough books, local meetups and international conferences. In free time I love to spend time with technical community, travel and ride a bicycle (or hit a gym in case of bad weather).
CodersRank Score
What is this?
This represents your current experience. It calculates by analyzing your connected repositories. By measuring your skills by your code, we are creating the ranking, so you can know how good are you comparing to another developers and what you have to improve to be better
Information on how to increase score and ranking details you can find in this blog post.
486.4
CodersRank Rank
Top 2%
Top 1
C++
Developer
Croatia
Top 5
Java
Developer
Croatia
Top 1
Rust
Developer
Croatia
Highest experience points: 0 points,
0 activities in the last year
Java
64.5
exp.
C++
126.2
exp.
Rust
77.2
exp.
Python
18.5
exp.
HTML
15.5
exp.
Jupyter Notebook
13.7
exp.
C
63.8
exp.
JavaScript
51.7
exp.
Shell
5.2
exp.
TypeScript
40
exp.
List your work history, including any contracts or internships
Self-employed
Oct 2018 - Aug 2020 (1 year 10 months)
Freelance Software Developer
TVbeat
Mar 2017 - Oct 2018 (1 year 7 months)
Data Integration Developer
Data integration for TV/Media companies, providing data analytic drivers.
Stack:
Lua, C/C++
Stack:
Lua, C/C++
Snowfall AB
Aug 2015 - Feb 2017 (1 year 6 months)
Senior Backend Developer
Developing Swedish MTR express web system.
Experienced:
Developed payment solution and seating policy for trains, with unit and integration tests.
Implemented real life train tracking trough websockets.
On frontend (AngularJS), with regular tasks, made angular bootstrap (without use of jQuery) work without bugs.
Experienced:
Developed payment solution and seating policy for trains, with unit and integration tests.
Implemented real life train tracking trough websockets.
On frontend (AngularJS), with regular tasks, made angular bootstrap (without use of jQuery) work without bugs.
Add some compelling projects here to demonstrate your experience
Udacity's Route Planning Project
Dec 2018 - Dec 2018
* Udacity C++ Nanodegree Foundations project
* Allow user input, A and B point containing x, y position
* Find shortest path using A* search algorithm
* Allow user input, A and B point containing x, y position
* Find shortest path using A* search algorithm
Udacity's System Monitor Project
Dec 2018 - Dec 2018
* Udacity C++ Nanodegree Object-Oriented Programming project
* Created single threaded system monitor, as a simple alternative to htop
* Goal was to learn basics of OOP in modern C++
* Created single threaded system monitor, as a simple alternative to htop
* Goal was to learn basics of OOP in modern C++
Udacity's Garbage Collector Project
Dec 2018 - Dec 2018
* Udacity C++ Nanodegree Memory Management project
* Wrote a custom simple smart pointer and tested for memory leaks
* In implementation there was needed to compare with standard smart pointers for functionality,
* Wrote a custom simple smart pointer and tested for memory leaks
* In implementation there was needed to compare with standard smart pointers for functionality,
This section lets you add any degrees or diplomas you have earned.
Udacity
Nanodegree, Self-Driving Car Engineer
Dec 2018 - Dec 2019
Udacity
Nanodegree, C++
Dec 2018 - Dec 2018
Udacity
Intel Edge AI Scholarship Foundation Course, Artificial Intelligence
Dec 2018 - Dec 2019
Edge in AI, means local (or near local) processing, as opposed to just anywhere in the cloud. This can be an actual local device like a smart refrigerator, or servers located as close as possible to the source.
Many applications with the cloud get data locally, send the data to the cloud, process it, and send it back. The edge means there’s no need to send to the cloud; it can often be more secure (depending on edge device security) and have less impact on a network. Edge AI algorithms can still be trained in the cloud, but get run at the edge.
Many applications with the cloud get data locally, send the data to the cloud, process it, and send it back. The edge means there’s no need to send to the cloud; it can often be more secure (depending on edge device security) and have less impact on a network. Edge AI algorithms can still be trained in the cloud, but get run at the edge.