10:00 – 17:00
Fundamentals of Machine Learning
Koolituse ajakava:
- 10:00 - 11:30 Koolitus
- 11:30 - 11:45 Kohvipaus
- 11:45 - 13:15 Koolitus
- 13:15 - 14:00 Lõuna
- 14:00 - 15:30 Koolitus
- 15:30 - 15:45 Kohvipaus
- 15:45 - 17:15 Koolitus
Kestus:
24 academic hours
Toimumiskoht:
Veebikoolitus
Toimumiskoht: Veebikoolitus
Eestikeelne lühitutvustus:
Masinõpe on andmeanalüüsi meetod, mis automatiseerib analüütilise mudeli koostamist. See on tehisintellekti haru, mis põhineb ideel, et süsteemid saavad andmetest õppida, mustreid tuvastada ja otsuseid langetada minimaalse inimese sekkumisega. Lihtsalt öeldes kasutatakse masinõppe algoritme, et leida mustreid suurtest andmemahtudest. Andmed hõlmavad kõiki numbreid, sõnu, pilte, klikke – ükskõik, mis andmed digitaalselt on, kõiki saab sööta masinõppe algoritmidele.
Masinõpet on võimalik rakendada igas ettevõttes, väikestest suurteni. Näiteks kasutavad masinõpet tuntud platvormid nagu Youtube, Netflix, Spotify, Facebook, Twitter – eesmärgiga pakkuda kasutajale temale paremat infovälja. Vaja on vaid andmebaase, mille kallal masinõpe toimetama panna. Täpsete mudelite loomisega on organisatsioonil parem võimalus tuvastada kasumlikud võimalused või vältida tundmatuid riske.
Koolitus toimub inglise keeles!
This 3-day course will enable you to better understand what Machine Learning is, including the fundamental practices and principles. It is an introduction to R and data analytics, with a deeper Introduction to Machine Learning. At the end of the course you'll be able to create simple Machine Learning models using Python and R.
Target audience: Aimed at people with existing technological and mathematical background looking to get a quick exposure to mathematics and techniques of Machine Learning.
The results of the training
At the end of this course attendees will know:
At the end of this course attendees will be able to:
Prerequisites to the course (recommended):
Delegates wish to take this course should have already completed 'Fundamentals of Data Science' or have the equivalent level of knowledge.
Length: 24 academic hours
The prerequisite for issuing the certificate is full participation in training.
The training topics:
Machine Learning with Python
The training price also includes:
teaching materials;
a trainer's consultation on the topics learned by e-mail after the training;
certificate.
Loe artiklit:
Michael began programming as a young child, and after freelancing as a teenager, he joined and ran a web start-up during university. Around studying physics and after graduating, he worked as an IT contractor: first in telecoms in 2011 on a cloud digital transformation project; then variously as an interim CTO, Technical Project Manager, Technical Architect and Developer for agile start-ups and multinationals.
His academic work on Machine Learning and Quantum Computation furthered an interest he now pursues as QA's Principal Technologist for Machine Learning. Joining QA in 2015, he authors and teaches programmes on computer science, mathematics and artificial intelligence; and co-owns the data science curriculum at QA.
Michael began programming as a young child, and after freelancing as a teenager, he joined and ran a web start-up during university. Around studying physics and after graduating, he worked as an IT contractor: first in telecoms in 2011 on a cloud digital transformation project; then variously as an interim CTO, Technical Project Manager, Technical Architect and Developer for agile start-ups and multinationals.
His academic work on Machine Learning and Quantum Computation furthered an interest he now pursues as QA's Principal Technologist for Machine Learning. Joining QA in 2015, he authors and teaches programmes on computer science, mathematics and artificial intelligence; and co-owns the data science curriculum at QA.
10:00 – 17:00
Fundamentals of Machine Learning
Koolituse ajakava:
Kestus:
24 academic hours
Toimumiskoht:
Veebikoolitus
Toimumiskoht: Veebikoolitus
Eestikeelne lühitutvustus:
Masinõpe on andmeanalüüsi meetod, mis automatiseerib analüütilise mudeli koostamist. See on tehisintellekti haru, mis põhineb ideel, et süsteemid saavad andmetest õppida, mustreid tuvastada ja otsuseid langetada minimaalse inimese sekkumisega. Lihtsalt öeldes kasutatakse masinõppe algoritme, et leida mustreid suurtest andmemahtudest. Andmed hõlmavad kõiki numbreid, sõnu, pilte, klikke – ükskõik, mis andmed digitaalselt on, kõiki saab sööta masinõppe algoritmidele.
Masinõpet on võimalik rakendada igas ettevõttes, väikestest suurteni. Näiteks kasutavad masinõpet tuntud platvormid nagu Youtube, Netflix, Spotify, Facebook, Twitter – eesmärgiga pakkuda kasutajale temale paremat infovälja. Vaja on vaid andmebaase, mille kallal masinõpe toimetama panna. Täpsete mudelite loomisega on organisatsioonil parem võimalus tuvastada kasumlikud võimalused või vältida tundmatuid riske.
Koolitus toimub inglise keeles!
This 3-day course will enable you to better understand what Machine Learning is, including the fundamental practices and principles. It is an introduction to R and data analytics, with a deeper Introduction to Machine Learning. At the end of the course you'll be able to create simple Machine Learning models using Python and R.
Target audience: Aimed at people with existing technological and mathematical background looking to get a quick exposure to mathematics and techniques of Machine Learning.
The results of the training
At the end of this course attendees will know:
At the end of this course attendees will be able to:
Prerequisites to the course (recommended):
Delegates wish to take this course should have already completed 'Fundamentals of Data Science' or have the equivalent level of knowledge.
Length: 24 academic hours
The prerequisite for issuing the certificate is full participation in training.
The training topics:
Machine Learning with Python
The training price also includes:
teaching materials;
a trainer's consultation on the topics learned by e-mail after the training;
certificate.
Loe artiklit:
Michael began programming as a young child, and after freelancing as a teenager, he joined and ran a web start-up during university. Around studying physics and after graduating, he worked as an IT contractor: first in telecoms in 2011 on a cloud digital transformation project; then variously as an interim CTO, Technical Project Manager, Technical Architect and Developer for agile start-ups and multinationals.
His academic work on Machine Learning and Quantum Computation furthered an interest he now pursues as QA's Principal Technologist for Machine Learning. Joining QA in 2015, he authors and teaches programmes on computer science, mathematics and artificial intelligence; and co-owns the data science curriculum at QA.
Michael began programming as a young child, and after freelancing as a teenager, he joined and ran a web start-up during university. Around studying physics and after graduating, he worked as an IT contractor: first in telecoms in 2011 on a cloud digital transformation project; then variously as an interim CTO, Technical Project Manager, Technical Architect and Developer for agile start-ups and multinationals.
His academic work on Machine Learning and Quantum Computation furthered an interest he now pursues as QA's Principal Technologist for Machine Learning. Joining QA in 2015, he authors and teaches programmes on computer science, mathematics and artificial intelligence; and co-owns the data science curriculum at QA.
10:00 – 17:00
Fundamentals of Machine Learning
Koolituse ajakava:
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Aadress
VeebikoolitusIT Koolitus | Vana-Lõuna 39/1, Tallinn | 6181727 | [email protected]