ⵉⵙⴼⴽⴰ ⵏ ⵉⵙⴼⴽⴰ & AI Bootcamp
ⵍⵎⴷ ⵜⵓⵙⵙⵏⵉⵡⵉⵏ ⵏ ⵉⵙⴼⴽⴰ ⴷ AI ⴳ ⵡⴰⵏⵜⵉⵔⵏⵉⵜ ⵙ ⴱⴰⵢⵜⵓⵏ, SQL, ⴷ ML. ⴱⵏⵏⵓ ⴰⵍⴳⵓⵔⵉⵜⵎ ⵉ ⵜⴰⵏⵏⴰⵢⵜ ⴷ NLP, ⴰⵔ ⵜⵙⵙⵓⵊⴰⴷ ⵉ ⵢⴰⵜ ⵜⵡⵓⵔⵉ ⵏ ⵜⵉⴽⵏⵓⵍⵓⵊⵉⵜ ⴳ 12 ⵏ ⵉⵎⴰⵍⴰⵙⵙⵏ ⴷⴰⵢ.
ⴰⵙⴱⴷ ⵖⵉⵍⴰⴷⴰⵢⵍⵍⵉ ⵔⴰⴷ ⵜⵍⵎⴷ
ⴰⵙⵎⵓⵜⵜⴳ ⵏ ⵢⴰⵏ ⵓⵖⴰⵡⴰⵙ ⵏ ⵓⵙⵙⵍⵎⴷ ⵉⵜⵜⵓⵙⵎⵔⴰⵙⵏ ⵙ ⵓⵥⵍⴰⵢ ⵏⵏⴰ ⵉⵜⵜⵓⵙⴽⴰⵔⵏ ⵃⵎⴰ ⴰⴷ ⴽⵏ ⴰⵡⵉⵏ ⵙⴳ ‘’ⵜⴳⴰ ⵢⴰⵜ ⵜⵖⴰⵡⵙⴰ ⵉⴼⵓⵍⴽⵉⵏ’’ ⴰⵔ ‘’ⵜⵙⴽⵔⴷ ⴰⵙⵍⴽⵉⵏ ⴽⵓⵍⵍⵓ’’ ⴳ ⵜⵓⵙⵙⵏⵉⵡⵉⵏ ⵏ ⵉⵙⴼⴽⴰ ⴳ 12 ⵏ ⵉⵎⴰⵍⴰⵙⵙⵏ (ⵜⵉⵣⵉ ⵏ ⵓⴽⵓⴷ).
Asɛuḍ n Data Analytics d Uheggi
Ad tebnuḍ tigejda idusen deg tasleḍt n isefka: ad d-tawiḍ, tesnadeḍ, tesfeḍeḍ akked theggiḍ isefka n tudert tikwal. S Pandas, ad tesyefseḍ azalen yellan, izuran (outliers), isefka ur nezgin d ifrdisen categorical, ad tessexdmeḍ tasleḍt statistique, akked usnulfu n visualisations akken ad tesnefleḍ isefka izgan ɣer isefka heggan i tasleḍt.
Talaft n Yimudal n Machine Learning Ihennun
Ad tissineḍ tamsedday n ML seg uheggi n isefka ɣer uɣellu, usenqed akked usnerni n yimudal n usugen. Ad tessexdmeḍ algorithmes supervised akked unsupervised, ad tqerreḍ gar-asen s tinaḍin n uzuzer, akked usnerni n tazgent s cross-validation, hyperparameter tuning akked ufran n umudel.
Talaft n Ifukan n Deep Learning d AI
Ad tesneḍ amek ẓẓayrent réseaux n neurons imoderna i AI. Seg iɣbula n réseaux n neurons artificial, ad d-tebnuḍ imudal n deep learning s PyTorch di lweqt-nni ad tesnadeḍ optimisation, regularisation, data augmentation, explainable AI akked generative models — tazmert tanamit i yisnasen imgur n AI.
Tazeṭṭa deg Computer Vision d NLP
Ad tesnadeḍ sin iɣunab imgur n AI. Ad d-tebnuḍ CNNs i uɛraḍ n twlafin, object detection akked segmentation, akked tissineḍ tarrayin n NLP am embeddings, réseaux n neurons yettuɣalen (RNN), transformers akked attention mechanisms i yinagrawen n AI yebnan ɣef uḍris.
Talaft n Isnasen Imoderna n AI d LLM
Ad tɛeddiḍ ML tamagit akken ad d-tebnuḍ isnasen yettwassedsen s LLM. Ad tesnadeḍ prompt engineering, LangChain, Retrieval-Augmented Generation (RAG) akked tamsedday n AI n tudert tikwal akken ad d-tesnulfuḍ imɛiwnen ihennun, inagrawen n tussna akked isnasen n generative AI heggan i production.
Aselken, Alqaḍ d Umgar n Yinagrawen n AI
Ad tawiḍ imudal n ML seg usnerni ɣer production. Ad tesselkeḍ s FastAPI, Docker akked ifukan n cloud, ad temgareḍ s Ray, akked alqaḍ n yimudal s MLflow — rnu ɣer taɣellist, tabaḍnit akked iḍfaren ifazen i yinagrawen n AI ittwattkalen deg tudert tikwal.
Bab 0: Amezruy (Pre-Work)
Data science d yiwet seg twuriwin ittwasertan aṭas deg iseggasen ineggura. Yeṭṭef ɣef usyefsi n isefka, asfeḍ-nsen, usenqed-nsen, d talaft n yimudal n machine learning i usugen n igmaḍ n tuddsiwin. Ɣef ddemma n taɣawsa-agi tarurant, aseɛeḍ-ines ilaq-as afham azuran deg waṭas n yifecka d tarrayin, am Python, systèmes, databases, tusnakt, d tigejda tussligt (linear algebra). Deg ubab-a, ad nawi iɣbula n data science akken a k-nheggi ad tebduḍ abrid-inek n uselmed.
Tazwart ɣer Python
- Tutlayt Python d umezruy-ines
- Iɣbula n Python
- Tigejda n isefka tigejdanin deg Python
- Classes d objects
- Modules d packages
- Input/Output
- Lɣelḍat d exceptions
Systèmes
- Systèmes n Python
- Anaconda
- Jupyter Notebooks
SQL d Databases
- Iɣbula n SQL
- Queries n SQL
Tigejda Tussligt (Linear Algebra)
- Scalars d vectors
- Matrices
- Norms
Git d GitHub
- Tazwart ɣer version control, workflow, asenqed n repositories, tiririt n ibeddilen, fetch d pull, push n ibeddilen
Asenfaṛ: Curve Fitting
- Asenfaṛ-agi yeṭṭef ɣef usefru n ugur n 'Curve Fitting', yeṭṭef ɣef unadi n tgetta ifazen i d-yemsaḍan ɣer isefka i d-yettunefken. Ad k-yawi ɣer umedya n ugur-agi yerna yebḍa ɣer tegzumin, yal tigzemt ad tesnerni iɣbula am OOP, SQL, Linear Algebra, d tamsedday taneggarut n Machine Learning
ⴰⵙⵖⵉⵡⵙ ⵏ ⵓⵙⵍⵎⴷ
ⵙⴳ ⵡⴰⵙⵙ ⵏ ⴰⵙⵉⵎⵡⴰⵙ ⴰⵔ ⴰⵙⵙ ⵏ ⵓⵙⵉⵎⵡⴰⵙ 9:30 ⵏ ⵜⴷⴳⴳⵯⴰⵜ ⴰⵔ 3:30 ⵏ ⵜⴷⴳⴳⵯⴰⵜ (ⴳⵎⵜ+1)
ⵜⴰⵖⵉⵎⵉⵜ ⵏ ⵓⵙⵔⴰⴳ ⵏ ⵜⵉⵏⴰⵡⵜ
9:30am - 11:00am
ⵜⴰⵖⵉⵎⵉⵜ ⵏ ⵓⵙⵔⴰⴳ ⵏ ⵜⵉⵏⴰⵡⵜ
11:30am - 01:00pm
ⴰⴼⵓⵙ-ⵉⵏ ⵙⵉⵙⵢⵓⵏ
02:00pm - 03:30pm
ⵜⴰⵎⴰⵎⴽⵜ ⵏⵏⵖ
ⴰⵙⵍⵎⴷ ⵏ ⵜⵓⴷⵔⵜ ⴳ ⵓⵏⵖⵎⵉⵙ
- ⴷⴰ ⴳ CLA, ⵙⵙⵎⵔⵙⵎ ⵜⴰⵔⵎⵉⵜ ⵏⵏⵓⵏ ⵏ ⵓⵙⵍⵎⴷ ⴰⴽⴷ ⵜⵡⵓⵔⵉⵡⵉⵏ ⵏⵏⵖ ⵜⵉⵎⵢⴰⵖⵉⵏ ⴳ ⵓⵏⵖⵎⵉⵙ ⴰⵏⴰⵎⵓⵔ, ⴰⵏⴷⴰ ⵔⴰⴷ ⵜⵙⴽⵔⵎ ⴰⵙⵔⵉⴷ ⴰⴽⴷ ⵉⵎⵙⵙⵍⵎⴷⵏ ⴷ ⵉⵎⴷⴷⵓⴽⴽⴰⵍ ⴳ ⵡⴰⴽⵓⴷ ⵏ ⵜⵉⴷⵜ, ⴰⵙⴱⵓⵖⵍⵓ ⵏ ⵓⵎⵢⴰⵡⴰⵙ ⴷ ⵓⵙⴱⵓⵖⵍⵓ ⵏ ⵜⵣⵎⵎⴰⵔ ⴰⵙⴷⴷⵔⴰⴼ.
ⵜⴰⵣⵔⴰⵡⵜ ⵏ ⵉⵅⴼ
- ⴰⵣⵎⵣ ⵏ ⵓⴳⵣⵣⵓⵎ: 9 ⵏ ⵜⵙⵔⴰⴳⵉⵏ ⵏ ⵓⵙⵍⵎⴷ ⴳ ⵓⵙⵍⵎⴷ, 11 ⵏ ⵜⵙⵔⴰⴳⵉⵏ ⵏ ⵜⵣⵔⴰⵡⵜ ⵜⴰⵏⵉⵎⴰⵏⵜ, 20 ⵏ ⵜⵙⵔⴰⴳⵉⵏ ⴳ ⴷⴷⵓⵢⵜ
- ⴰⴽⵓⴷ ⴽⵓⵍⵍⵓ: 22,5 ⵏ ⵜⵙⵔⴰⴳⵉⵏ ⴳ ⵓⵙⵍⵎⴷ ⴰⵏⴰⵎⵓⵔ, 17,5 ⵏ ⵜⵙⵔⴰⴳⵉⵏ ⵏ ⵜⵣⵔⴰⵡⵜ ⵜⴰⵏⵉⵎⴰⵏⵜ, ⴰⵙⵖⵍ ⵏ 40 ⵏ ⵜⵙⵔⴰⴳⵜ ⴳ ⴷⴷⵓⵢⵜ
ⴰⵙⵖⵍ ⵏ ⵜⵉⵏⵎⵍ
- ⵜⵉⵔⵎⵉⵜ ⵏ ⵢⴰⵏ ⵓⴱⵔⵉⴷ ⵏ ⵓⵙⵍⵎⴷ ⴰⴷⵉⵏⴰⵎⵉⴽ ⴰⴽⴷ ⵜⵖⴰⵔⴰⵙⵜ ⵏⵏⵖ ⵏ ⵜⵉⵏⵎⵍ ⵍⵍⵉ ⵏⵏ ⵉⵜⵜⵓⵙⵎⵔⴰⵙⵏ, ⴰⵔ ⴽⵏ ⵢⴰⵊⵊ ⴰⴷ ⵜⵍⵎⴷⵎ ⵙ ⵜⵖⴰⵔⴰⵙⵜ ⵉⵖⵓⴷⴰⵏ ⴷ ⴰⴷ ⵜⴽⵛⵎⵎ ⵙ ⵢⴰⵜ ⵜⵖⴰⵔⴰⵙⵜ ⵉⴼⵓⵍⴽⵉⵏ ⴳ ⵓⵖⴰⵡⴰⵙ ⵏⵏⵖ ⵏ ⵓⵏⴳⵔⴰⵡ ⵏ ⴱⵓⵜⴽⴰⵎⴱ.
ⵜⴰⵎⵙⴽⵉⵔⵜ ⵜⴰⵏⵎⵀⴰⵍⵜ
- ⴰⵙⴽⵛⵎ ⴳ ⵢⴰⵜ ⵜⵉⵔⵎⵉⵜ ⵏ ⵓⵍⵎⵎⵓⴷ ⵍⵍⵉ ⵔⴰⴷ ⵢⴰⵊⵊ ⴰⴷ ⵏⵙⴽⵔ ⴰⵙⵎⵓⵜⵜⴳ ⴳ ⴱⵓⵜⴽⴰⵎⴱ ⵏⵏⵖ, ⵍⵍⵉ ⴳ ⵏⵜⵜⵙⴽⴰⵔ ⴰⵙⴽⵙⵡ ⵅⴼ ⵜⴷⵔⴰⵡⵜ ⵜⴰⵏⴼⴳⴰⵏⵜ, ⴰⵙⵎⵓⵜⵜⴳ ⵏ ⵉⴼⴰⵙⵙⵏ, ⴷ ⵓⵥⴽⴽⴰ ⵏ ⵓⴼⵜⴰⵙ ⴰⴼⴰⴷ ⴰⴷ ⵏⵙⵙⴽⵔ ⵢⴰⵜ ⵜⵙⵉⵍⴰ ⵉⵖⵓⴷⴰⵏ ⵉ ⵜⵓⵙⵙⵏⴰ ⵏⵏⵓⵏ.
Tebɣiḍ ad teslemd s tɣuri-k?
Teslemd s On‑demand Data Science & AI course s tɣuri-k, s tferḍit meṛṛa. Sseqdec-d amek ad tessnifeḍ data imeqqranen ɣer insights i yesεan azal, ad tsellemd models iḥerfanen, ad tebnuḍ iseqdacen AI n tidett, rnu ad temsileḍ theggaḍ i wakken ad tebduḍ tkarir-ik deg umaḍal n data‑driven innovation.
Issin ugar
ⴰⵢⵏⵏⴰ ⵔⴰⴷ ⴽ ⵢⴰⵊⵊ
ⵓⵔ ⵜⵃⵡⴰⵊⴻⵎ ⴽⵔⴰ ⵏ ⵢⵉⵣⵡⴰⵍ ⵉⵣⴰⵢⴷⴻⵏ ⴷⴻⴳ ⵜⵓⵙⵙⵏⵉⵡⵉⵏ ⵏ ⵓⵎⴻⵙⵏⵉ ⵏⴻⵖ ⴷⴻⴳ ⵓⵀⴻⵢⵢⵉ ⴰⴽⴽⴻⵏ ⴰⴷ ⵜⴻⵜⵜⴻⴽⴽⵉⵎ ⴷⴻⴳ-ⵙ. ⵓⵔ ⵏⴻⵜⵜⵄⴻⵟⵟⵉⵍ ⴰⵔⴰ ⴽⵔⴰ ⵏ ⵜⵓⵙⵙⵏⴰ ⵜⴰⵣⵡⴰⵔⴰⵏⵜ ⵢⴻⵔⵏⵓ ⴰⴷ ⴽⴻⵏ-ⵏⴻⵙⵙⴻⵇⴷⴻⵛ ⵙ ⵜⵍⴻⵎⵎⵉⵥⵉⵏ ⴷⴻⴳ ⴽⵔⴰ ⵏ ⵢⵉⵙⵔⴰⴳⴻⵏ ⵉⵎⴻⵣⵡⵓⵔⴰ, ⴷ ⴰⵢⴻⵏ ⴰⵔⴰ ⴽⴻⵏ-ⵢⴻⴵⴵⴻⵏ ⴰⴷ ⵜⴱⵏⵓⵏ ⵜⴰⵙⵉⵍⴰ ⵉⵊⴻⵀⴷⴻⵏ ⵙⴻⴳ ⵢⵉⴷⵉⵙ ⵏ ⵓⵏⵔⴰⵔ. ⵎⴽ ⵍⵍⵉ ⵜⴳⴰⵎ ⴰⵎⴰⵢⵏⵓ ⴳ ⵓⵏⵔⴰⵔ ⵏⵖ ⴰⵔ ⵜⵔⵣⵣⵓⵎ ⵅⴼ ⵢⴰⵏ ⵓⵙⵏⴼⵍ ⵏ ⵜⵡⵓⵔⵉ, ⴰⵔ ⵉⵜⵜⵓⵙⴽⴰⵔ ⵓⵖⴰⵡⴰⵙ ⵏⵏⵖ ⴰⴼⴰⴷ ⴰⴷ ⴽⵏ ⵢⴰⴷⵊ ⴰⴷ ⴽⵏ ⵢⴰⴷⵊ ⴰⴷ ⴽⵏ ⵢⴰⴷⵊ ⴰⴷ ⵜⵏ ⵜⵙⴽⵔⵎ ⵙ ⵢⴰⵜ ⵜⵖⴰⵔⴰⵙⵜ ⵉⵣⴷⴷⵉⴳⵏ ⴷ ⵉⴼⵓⵍⴽⵉⵏ
- ⵍⴰⵒⵜⵒ ⵏⴻⵖ ⴰⵎⵙⵙⵓⴷⵙ: ⴰⵙⴻⵍⴽⵉⵎ ⵏ ⵍⴰⵒⵜⵓⵒ ⵏⴻⵖ ⴰⵙⴻⵍⴽⵉⵎ ⵏ ⵓⵏⴻⵔⵎⵉⵙ ⵢⴻⵙⵄⴰⵏ ⵜⴰⵣⵎⴻⵔⵜ ⵏ ⵓⵙⴻⵎⵔⴻⵙ ⵉⵡⴰⵜⴰⵏ ⵢⴻⵔⵏⵓ ⵢⴻⵣⵎⴻⵔ ⴰⴷ ⵢⴻⵙⵙⴻⴼⵔⴻⴽ ⴰⵀⵉⵍⴻⵏ ⴰⵢ ⵢⴻⵙⵙⴻⴼⴽⴻⵏ.
- ⴰⵙⴱⴷⴰⴷ ⵏ ⵉⵏⵜⵔⵏⵜ ⴱⴹⵓ: ⴰⵙⴽⵛⵎ ⵏ ⵉⵏⵜⵔⵏⵜ ⵍⵍⵉ ⵔⴰⴷ ⵢⴰⵊⵊ ⴰⴷ ⵏⵙⴽⵔ ⴰⵙⵎⵓⵜⵜⴳ ⵏ ⵉⵏⵖⵎⵉⵙⵏ ⵙ ⵜⵉⴷⵜ, ⵉⵙⴰⵔⴰⵎⵏ ⵏ ⵉⴼⴰⵙⵙⵏ, ⴷ ⵜⵡⵓⵔⵉⵡⵉⵏ.
- ⴰⵙⵍⵎⴷ ⴰⴷⵙⵍⴰⵏ ⵏ ⵓⵎⵙⵙⵓⴷⵙ: ⵜⴰⵣⵎⵔⵜ ⵏ ⵓⵙⵡⵓⴷⴷⵓ ⵏ ⵉⵏⴳⵔⴰⵡⵏ ⵏ ⵓⵙⵡⵓⵔⵉ, ⴰⵙⵖⵉⵡⵙ ⵏ ⵓⴼⴰⵔⵙ, ⴷ ⵉⵎⵙⵙⵓⴷⵙⵏ ⵏ ⵉⵏⵜⵔⵏⵜ.
- ⵜⵓⵙⵙⵏⴰ ⵜⴰⴷⵙⵍⴰⵏⵜ ⴳ ⴰⵍⴳⵓⵔⵉⵜⵎⵉⴽ ⴷ ⵓⵙⵖⵉⵡⵙ: ⴰⵙⵢⴰⴼⴰ ⵙ ⵉⵔⵎⵎⵓⵙⵏ ⵏ ⵓⵙⵖⵉⵡⵙ ⵃⵎⴰ ⴰⴷ ⴹⴼⵓⵕⵏ ⵉⵎⵓⴽⴰⵏ ⵙ ⵜⵏⴼⵍⵉⵜ.
- ⴰⵏⴳⵍⵉⵣ ⴰⵏⴳⵍⵉⵣⵉ: ⴰⵙⵡⵉⵔ ⵏ B1 ⵙ ⵜⵣⵎⵔⵜ ⵏ ⵓⵔⵎⴰⵙ ⵏ ⵜⵎⵜⵜⵉⵡⵉⵏ ⵜⵉⵜⵉⴽⵏⵉⵢⵉⵏ ⴷ ⵓⵎⵢⴰⵡⴰⴹ ⵙ ⵜⵖⴰⵔⴰⵙⵜ ⵉⵖⵓⴷⴰⵏ, ⴰⵛⴽⵓ ⴷⴰ ⵉⵜⵜⵓⵙⴽⴰⵔ ⵓⵏⴳⵔⴰⵡ ⵏ ⴱⵓⵜⴽⴰⵎⴱ ⵙ ⵜⵓⵜⵍⴰⵢⵜ ⵜⴰⵏⴳⵍⵉⵣⵉⵜ.
- ⴰⵙⵎⵖⵔ ⵏ ⵓⵙⵍⵎⴷ: ⵢⴰⵏ ⵡⴰⴷⴷⴰⴷ ⴰⵏⴼⵔⴰⴽ ⵖⵔ ⵓⵙⵍⵎⴷ ⴷ ⵓⵙⵏⴼⵍⵓⵍ ⵏ ⵓⴽⵓⴷ, ⵙⵍⴰⵡⴰⵏ ⴰⴽⴽⵡ ⴳ ⵜⵉⵣⵉ ⵏ ⵓⵣⵡⴰⵔ ⴰⴼⴰⴷ ⴰⴷ ⵏⵙⴱⴷⴻⴷ ⵢⴰⵜ ⵜⵙⵉⵍⴰ ⵉⵖⵓⴷⴰⵏ ⵉ ⵓⴽⵎⵎⵍ ⴳ ⴱⵓⵜⴽⴰⵎⴱ.
ⴰⴼⴰⴷ ⴰⴷ ⵜⴼⵔⵓⵎ ⵉⵙⵏⵓⵎⵎⴰⵍ ⵏ ⵓⵥⵕⴼ ⴰⵎⵓⴼⴰⵢ
ⵓⵔ ⵜⵜⴻⵊⵊⵉⵜ ⵉⴷⵔⵉⵎⴻⵏ ⴰⴷ ⴽⴻⵏ-ⵜ-ⵉⴷ-ⵜⴻⵙⵙⴻⵔⵙⴻⵎ ⴰⴽⴽⴻⵏ ⴰⴷ ⵜⴽⴻⵎⵎⵍⴻⵎ ⵖⴻⵔ ⵓⵜⴰⵔⴰⵎ-ⵏⵏⴻⵖ. ⴰⵔ ⵏⵙⴼⵙⴰⵢ ⴽⵓ ⵜⵉⴽⴽⵍⵜ ⵉⴼⵙⵙⴰⵢⵏ ⵏ ⵓⵙⴼⵍⵙ ⵉⴼⵓⵍⴽⵉⵏ ⴷ ⵜⵣⵎⵎⴰⵔ ⵏ ⵓⵙⴷⵔⵉⵎ ⵃⵎⴰ ⴰⴷ ⵏⵙⴽⵔ ⵉⵖⴰⵡⴰⵙⵏ ⵏⵏⵖ ⵉ ⴽⵓ ⵢⴰⵏ.
ⴰⵙⴼⵙⵔ ⵏ ⵉⵙⵜⴰⵢⵏ ⵏ ⵓⵥⵕⴼ
ⴰⵎⵎⴰⵙ ⵏ ⵜⵡⵓⵔⵉⵡⵉⵏ ⵏ ⵜⵡⵓⵔⵉ
ⵜⵉⵡⵓⵔⵉⵡⵉⵏ ⵏ ⵓⵙⴱⵓⵖⵍⵓ ⵏ ⵜⵡⵓⵔⵉ
ⵜⵉⵖⵉⵎⵉⵜⵉⵏ ⵏ ⵜⵡⵓⵔⵉ ⵖⵓⵔⵓⵏ ⴷ ⵜⴳⵔⴰⵡⵜ ⵏ CLA ⵍⵍⵉ ⴱⴰⵀⵔⴰ ⵉⵜⵜⵓⵙⵎⵔⴰⵙⵏ. ⵙⵙⵎⵔⵙ ⴰⵢⵍⵍⵉ ⴷ ⵉⵙⵙⵓⵎⵔ ⵡⴰⵎⵎⴰⵙ ⵏⵏⵖ ⵏ ⵜⵡⵓⵔⵉ, ⴰⴷ ⵏⵙⵎⴽⵍ ⴰⵙⵎⵙⴰⵙⴰ ⵏⵏⵖ ⵏ ⵜⵡⵓⵔⵉ ⴰⵔ ⵜⵏ ⵜⵜⴰⵣⵣⴰⵍⴷ ⴳ ⵢⴰⵜ ⵜⵙⵓⵜⵍⵜ ⵉ ⵡⵉⵍⵍⵉ ⵉⵣⵔⵉⵏ ⴳ ⵜⵙⵔⴰⴳⵜ ⵜⴰⵏⴳⴳⴰⵔⵓⵜ.
ⴰⵙⴳⵔⴰⵡ ⵏ ⵓⵙⵎⵓⵜⵜⴳ ⵏ ⵜⵡⵓⵔⵉ ⵏ ⵜⵡⵓⵔⵉ
ⵜⵉⵡⵓⵔⵉⵡⵉⵏ ⵏ ⵓⵙⵏⵓⵍⴼⵓ ⵉ ⵓⵙⵡⵓⵜⵜⵓ ⵏ ⵉⵙⵓⵖⴰⴷ ⵏⵏⵓⵏ ⵏ ⵜⵡⵓⵔⵉ ⴷ ⵓⵙⵏⵓⵍⴼⵓ ⵏ ⵜⵙⵜⵔⴰⵜⵉⵊⵉⵢⵉⵏ ⵃⵎⴰ ⴰⴷ ⵜⵏ ⵜⵙⴽⵔⵎ ⵙ ⵜⵡⵓⵔⵉⵡⵉⵏ ⵏ ⵓⵙⵎⴽⵍ ⴰⵏⴰⵎⵓⵏ ⵏⵖ ⵙ ⵓⵙⵖⵉⵡⵙ ⵏ ⵜⵡⵓⵔⵉ ⵏ ⵜⵡⵓⵔⵉ.
Mock Intermanes
ⴰⵔ ⵜⵜⵓⵙⴽⴰⵔⵏⵜ ⵉⵙⵇⵙⵉⵜⵏ ⵏ ⵜⵉⴽⵍⵉ ⵏ ⵓⵎⵙⴰⵡⴰⵍ ⵉⵛⵛⴰⵔⵏ ⵏⵏⴰ ⴷ ⵉⵙⵙⴽⴰⵏⵏ; ⵎⴰⵎⴽ ⵔⴰⴷ ⵜⴼⴽⵎ ⴰⵢⵍⵍⵉ ⵔⴰⴷ ⴽⵏ ⵢⴰⵊⵊ ⴰⴷ ⵜⴼⴽⵎ ⵉ ⵉⵎⵙⵡⵓⵔⵉⵜⵏ, ⵎⴰⵎⴽ ⵔⴰⴷ ⵜⵙⴽⵔⵎ ⴰⵙⵖⵍ ⵏⵏⵓⵏ, ⵎⴰⵎⴽ ⵔⴰⴷ ⵜⵙⴽⵔⵎ ⴰⵙⵖⵍ ⵏ ⵜⵡⵓⵔⵉ ⴷ ⵡⵉⵢⵢⴰⴹ.
ⴰⵙⴽⴽⵉⵍ ⵏ resume & Cover views
ⴰⵔ ⵜⵜⴰⵡⵉⵏ ⵉⵙⵓⵎⴰⵔ ⵉⵏⴼⴳⴰⵏⵏ ⵅⴼ ⵓⵙⵎⵍ ⵏⵏⵓⵏ ⵏⵖ ⵜⴰⴱⵔⴰⵜ ⵏⵏⵓⵏ ⵏ ⵜⴼⵍⵡⵉⵜ, ⴰⵔ ⵜⵙⵏⵓⵎⵎⴰⵍⵎ ⴰⴷ ⵜⴰⵡⵉⵎ ⴰⵙⴽⵙⵡ ⵏ ⵉⵎⵙⵡⵓⵔⵉⵜⵏ ⴷ ⴰⴷ ⵜⵙⴽⵔⵎ ⵢⴰⵏ ⵓⵎⵙⴰⵡⴰⵍ ⴳ ⵜⵡⵓⵔⵉ ⵏⵏⴰ ⵜⵔⴰⵎ.
ⵊⵓⴱ ⴷ ⵉⵏⵜⵔⵏⵉⴱ ⵔⵓⵓⵏⴷ-ⵓⴱ
ⵜⵉⵣⵎⵎⴰⵔ ⵜⵉⵎⴰⵢⵏⵓⵜⵉⵏ ⵏ ⵓⵅⴷⴷⵉⵎ, ⵙ ⵓⴼⵓⵙ ⵏⵏⴰ ⴼⴽⵉⵏ ⵉⵎⵥⵍⴰⵢⵏ ⵏⵏⵖ ⵏ ⵜⵡⵓⵔⵉ, ⴰⵔ ⵜⵜⵓⵙⴽⴰⵔⵏⵜ ⵙ ⵜⵉⴷⵜ ⴳ ⵓⵙⵡⵉⵔ ⵏ ⵓⴽⵛⵛⵓⵎ ⵙ ⵜⵉⴷⵜ.
ⴰⵙⵖⵍ ⵏ ⵉⵙⵓⴳⴰⵎ ⵏ ⵜⵡⵓⵔⵉ
ⴰⵔⵥⵥⵓⵎ ⵏ ⵓⵙⴽⵛⵎ ⵖⵔ ⵜⵙⵏⵓⵔⴰⵢⵜ ⵏⵏⵖ ⵏ ⵜⵡⵓⵔⵉ ⵏ ⵜⵡⵓⵔⵉ ⵏ ⵜⵡⵓⵔⵉ ⵏ ⵜⵡⵓⵔⵉ ⵏ ⵜⵡⵓⵔⵉ, ⴷ ⵜⵡⵓⵔⵉⵡⵉⵏ ⵏ ⵜⵎⴳⵓⵔⵉ ⵏ ⵜⵉⴽⵏⵓⵍⵓⵊⵉⵜ.
ⴰⵙⵖⵍ ⴰⵣⵓⵍⴰⵏ ⴷ ⵉⵏⵖⵎⵉⵙⵏ ⵏ ⵓⵥⵟⵟⴰ
ⵎⵍⴰⵍ ⴷ ⵉⵎⵙⵡⵓⵔⵉⵜⵏ ⵏ ⵜⵉⴽⵏⵓⵍⵓⵊⵉⵜ ⴳ ⵜⵎⴳⵓⵔⵉ ⵏⵏⵓⵏ ⵃⵎⴰ ⴰⴷ ⵜⴰⵡⴹⵎ ⴰⵙⴼⵙⵔ ⵏ ⵜⵡⵓⵔⵉ ⴷ ⵓⵙⵏⵎⴰⵍⴰ, ⵓⵍⴰ ⴰⵣⵎⵣ ⵏ ⵓⵙⵎⵔⵙ ⵏ ⵉⵎⵣⵣⵓⵍⵏ ⵢⴰⴹⵏⵉⵏ ⴳ ⵉⵎⵓⵙⵙⵓⵜⵏ ⵏⵏⵖ ⵏ ⴽⴰⵔⵉⵔ ⵛⴰⵜ.
ⴰⵏⵎⴰⵣⵓⵍ ⵏ ⵓⵥⵟⵟⴰ
ⴰⵣⴷⴰⵢ ⴰⴽⴷ ⵉⵎⴷⴷⵓⴽⴽⴰⵍ ⵏ ⵜⵉⵏⵎⵍ ⴷ ⵉⵏⵍⵎⴰⴷⵏ ⵉⵣⵔⵉⵏ ⵏ CLA ⵃⵎⴰ ⴰⴷ ⴱⴹⵓⵏ ⴰⵙⵓⵎⵔ ⵉⴼⵓⵍⴽⵉⵏ ⴷ ⵉⵣⴷⵉⵏ, ⴰⴷ ⵏⴱⴷⵓ ⴰⵙⵎⵔⴰⵔⴰ ⵏ ⵡⴰⵡⴰⵍ ⵉⴼⵓⵍⴽⵉⵏ, ⴷ ⴰⴷ ⴱⴹⵓⵏ ⵉⵕⵥⴰⵎⵏ ⵏ ⵜⵡⵓⵔⵉ ⵏⵏⴰ ⵉⵖⵉⵏ ⴰⴷ ⵉⴳ ⴰⵏⴰⵔⵓⵣ ⵉ ⵉⵎⴷⴷⵓⴽⴽⴰⵍ ⵏⵏⵙ ⵉⵎⵣⵔⴰⵡⵏ.
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1-to-1 ⴰⵙⵎⵓⵜⵜⴳ ⵏ ⵜⵡⵓⵔⵉ
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ⴰⵙⴷⵓⵙ ⵏ ⴰⵎⵓⵔⴰⵙ (Portfolio)
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ⴰⵙⵍⵎⴷ ⵏ ⵜⵓⵏⵚⵉⴱⵜ
ⴰⴳⵔⴰⴹ ⵏ AI, ⴰⵙⴳⵔ ⵏ cyber ⴰⵙⴳⵔⵓ ⴷ web dev, ⵜⵙⴳⵯⵔⴰⵏ ⴰⴽⴼⵔⴰⵏ ⵉⵖⵔⵉⵏ.
ⵜⴰⵙⵍⴽⵉⵏⵜ ⵉⵖⵔⵉ
AZAV-ⴰⴽⵔⴻⴷ Code Labs Academy ⵜⴰⵙⵍⴽⵉⵏⵜ, ⴰⵙⵍⵎⴷ LinkedIn, CV ⴷ ⴰⵎⴰⵙⴽⵓⵏ visa.
ⵉⵙⵇⵙⵉⵜⵏ ⵉⵜⵜⵓⵙⴽⴰⵔⵏ ⵙ ⵜⵎⵇⴱⵜ ⵉⵙⵇⵙⵉⵜⵏ
ⵜⴰⵏⵙⵉⵎⵏ ⵏ Code Labs Academy ⵉⵎⴰⴽ ⵏ ⴰⵎⴰⵙⴽⵓⵏ
ⵎⵉ ⴽⴽⵙⴻⵖ ⵍⴱⴰⴽⵉⵏⵓ ⴷⴻⴳ ⵜⴻⵙⵏⵉⵍⴻⵙⵜ ⵏ ⵢⵉⵙⴻⴼⴽⴰ, ⵙⵙⴰⵡⴹⴻⵖ ⴰⴷ ⵙⵏⴻⵔⵏⵉⵖ ⵜⴰⵎⵓⵙⵙⵏⵉⵉⵏⵓ ⴷⴻⴳ ⵓⵏⵏⴰⵔⴰ ⵙ ⵢⵉⵙⵡⵉ ⵏ ⵓⴹⴼⴰⵔ ⵏ ⵜⵎⵓⵙⵙⵏⵉ ⴰⵎⴰ ⴷⴻⴳ ⵜⵓⵙⵙⵏⴰ ⵏ ⵢⵉⵙⴻⴼⴽⴰ ⵏⴻⵖ ⴷⴻⴳ ⵜⴻⵙⵏⵉⵍⴻⵙⵜ. ⴷ ⴰⵛⵓ ⴽⴰⵏ, ⵎⵇⴰⴱⴰⵍⴻⵖ ⴷ ⵡⵓⴳⵓⵔⴻⵏ ⴰⴽⴽⴻⵏ ⴰⴷ ⴷⴰⴼⴻⵖ ⵜⵉⵡⵡⵓⵔⴰ ⵖⴻⴼ ⵢⵉⵙⴻⵙⵜⴰⵏⴻⵏⵉⵏⵓ, ⴷⵖⴰ ⵏⵓⴷⴰⵏⴷ ⵖⴻⴼ ⵢⵉⵡⴻⵏ ⵏ ⵓ ...
ⵜⴰⵣⵔⴰⵡⵜ ⵏ ⵓⵙⵏⴻⵔⵏⵉ ⵏ ⵡⴻⴱ ⵏ Code Labs Academy ⵜⴻⵍⵍⴰⴷ ⵙ ⵡⴰⵣⴰⵍⵉⵙ ⴰⵟⴰⵙ, ⴷ ⵢⵉⵡⴻⵜ ⵙⴻⴳ ⵜⵎⵓⵖⵍⵉⵡⵉⵏ ⵜⵉⴳⴻⵔⵔⵣⴻⵏ ⴰⴽⴽ ⴰⵢ ⵙⵄⵉⵖ ⴷⴻⴳ ⵜⵓⴷⴻⵔⵜⵉⵡ. ⵏⴻⴽⴽ ⵙⵙⵓⵜⵓⵔⴻⵖⴰⴽ ⴰⵟⴰⵙ ⴰⴷ ⵜⵃⴻⴷⴷⵔⴻⴹ ⴷⴻⴳ bootcampa ⴰⵏⴷⴰ ⵓⵔ ⵜⵍⴻⵎⴷⴻⴹ ⴰⵔⴰ ⴽⴰⵏ ⴰⵙⵏⴻⵔⵏⵉ ⵏ ⵡⴻⴱ, ⵎⴰⵛⴰ ⴰⴷ ⴷⵜⴰⴼⴻⴹ ⴷⴰⵖⴻⵏ ⵉⵡⴻⵍⵍⵉⵀⴻⵏ ⵏ ⵜⵖⴰⵡⵙⵉ ...
ⵏⴻⴽⴽ ⵜⵜⵏⴰⴷⵉⵖ ⴷⵉⵎⴰ ⵖⴻⴼ ⵜⴻⴳⵏⵉⵜ ⵜⴰⵎⴰⵢⵏⵓⵜ ⴰⴽⴽⴻⵏ ⴰⴷ ⵍⴻⵎⴷⴻⵖ ⵜⵉⵥⵡⴰⵔ ⵜⵉⵎⴰⵢⵏⵓⵜⵉⵏ ⴷⴻⴳ Tussna ⵏ Yisefka, ⵢⴻⵔⵏⴰ ⵍⵇⵉⵎⴰ ⵏ ⵜⵖⴰⵡⵙⵉⵡⵉⵏ ⵏ Code Labs Academy ⵜⴻⵣⴳⴻⵔ ⴰⵢⴻⵏ ⴰⵢ ⵜⵜⵕⴰⴵⵓⵖ. ⵎⴰ ⵢⴻⵍⵍⴰ ⵜⵃⴻⵎⵎⵍⴻⴹ teknoloji ⵢⴻⵔⵏⴰ ⵜⴻⴱⵖⵉⴹ ⴰⴷ ⵜⴻⵙⵙⴻⴽⵏⴻⴹ ⵍⴵⴻⵀⴷ, bootcampa ⴰⴷ ⴰⴽⵢⴻⵍⴷⵉ ⵜⵉⵡⵡⵓⵔ ...
ⵎⴻⴱⵍⴰ ⵎⴰ ⵙⵄⵉⵖ ⵍⴱⴰⴹⵏⴰ ⵏ ⵜⴻⵙⵏⴰⵜⵡⵉⵍⵜ (technologie), ⴷⴻⴼⴼⵉⵔ ⴽⵔⴰ ⴽⴰⵏ ⵏ ⵡⴰⵢⵢⵓⵔⴻⵏ, ⵓⵔ ⵣⵎⵉⵔⴻⵖ ⴰⵔⴰ ⵜⵓⵔⴰ ⴰⴷ ⴼⴻⵀⵎⴻⵖ ⴽⴰⵏ ⵉⵎⵓⴷⴻⵍ ⵏ ⵜⵎⴰⵛⵉⵏⵉⵏ ⵏⴻⵖ ⵏ ⵓⵍⵎⴰⴷ ⴰⵍⵇⴰⵢⴰⵏ ⵉⵅⵓⵚⵚⴻⵏ, ⵡⴰⵏⴰⴳ ⵣⴻⵎⵔⴻⵖ ⴷⴰⵖⴻⵏ ⴰⴷ ⵜⴻⵏⵙⵏⵓⵍⴼⵓⵖ ⵙ ⵜⵉⵎⵎⴰⴷⵉⵡ. ⵎⴰ ⵢⴻⵍⵍⴰ ⵜⴻⵜⵜⵏⴰⴷⵉⴹ ⵖⴻⴼ ⵓⴱⴻⴷⴷⴻⵍ ⵏ ⵜⵎⵓⵙⵏⵉ ⴷⴻⴳ ⵜⴻⵎⴳⵓ ...
ⵉⵙⴻⵍⵎⴰⴷⴻⵏ ⴷ ⵢⵉⵎⴻⵙⵏⴰⵍⵍⵓⵏⴻⵏ ⴷ ⵉⴳⴻⵔⵔⵣⴻⵏ, ⵎⴰ ⵓⵍⴰⵛ ⵡⵉⵏ ⵙⵄⵉⵖ. Moe ⵢⴻⵙⵙⴻⵍⵎⴻⴷⵉⵢⵉ ⵓⴳⴰⵔ ⵏ ⵡⴰⴽⴽ ⵉⵙⴻⵍⵎⴰⴷⴻⵏⵉⵡ ⴷⵉ ⵜⵓⴷⴻⵔⵜⵉⵡ ⵎⴻⵕⵕⴰ. ⵢⴻⵜⵙⴱⴻⴳⴳⵉⵏ- ⴻⴷ ⵍⵃⴰⴵⴰ ⵢⴻⵔⵏⴰ ⵢⴻⵙⵙⴻⴱⵖⴰⵙ- ⵉⴽ ⴷⵉⵎⴰ ⴰⴽⴽⴻⵏ ⴰⵜⵙ- ⵜⵙⴽⴻⵎⵍⴻⴹ ⴰⴱⵔⵉⴷ- ⵉⴽ ⵖⴰⵙ ⴰⴽⴽⴻⵏ ⵍⵍⴰⵏ ⵡⵓⴳⵓⵔⴻⵏ.
ⵢⵉⵡⴻⵏ ⵙⴻⴳ ⵢⵉⴱⴻⵔⴷⴰⵏ ⵉⴳⴻⵔⵔⵣⴻⵏ ⴰⴽⴽⴻⵏ ⴰⴷ ⵜⵍⴻⵎⴷⴻⴹ Tussna ⵏ Data ⴷ Machine Learning, ⵉⵙⴻⵍⵎⴰⴷⴻⵏ ⵉⴼⴰⵣⴻⵏ ⵉ ⴽⵉⵄⴰⵡⵏⴻⵏ ⴷⵉⵎⴰ ⴰⴷ ⵜⴼⴻⵀⵎⴻⴹ ⵢⴻⵔⵏⴰ ⴰⴷ ⴰⴽⴷ-ⴼⴽⴻⵏ ⵓⴳⴰⵔ ⵏ ⵜⴻⴽⵜⵉⵡⵉⵏ ⴷ ⵢⵉⵎⴻⴷⵢⴰⵜⴻⵏ. ⵎⴰ ⵜⴻⴱⵖⵉⴹ ⴰⴷ ⵜⵉⵙⵙⵉⵏⴻⴹ ⵓⴳⴰⵔ ⵖⴻⴼ ML, CLA ⴷ ⴰⵎⴽⴰⵏ ⵉⴳⴻⵔⵔⵣⴻⵏ.
ⴷ boot camp ⴷⴻⴳ ⵓⵙⵎⴻⵍ ⵙ ⵜⴽⵓⵔⵙⵉⵡⵉⵏ asynchrones ⵉⵣⴻⵎⵔⴻⵏ ⴰⴷ ⵎⵇⴰⴱⴰⵍⴻⵏⵜ ⴷ ⵢⴰⵍ ⴰⵏⴻⵍⵎⴰⴷ ⴷⴻⴳ ⵓⵎⴰⴹⴰⵍ ⵎⴻⵕⵕⴰ. ⵏⴻⴽⴽ ⵜⵜⵇⴰⴷⴰⵔⴻⵖ ⵉⵎⵉ ⵢⴻⵜⵜⴰⵙⴷ ⵙ ⵜⵙⴻⵍⴽⵉⵏⵜ ⴷⴻⴳ ⵜⴰⴳⴳⴰⵔⴰ ⵎⵉ ⴰⵔⴰ ⵢⴻⴽⴼⵓ ⵙ ⵔⵔⴱⴻⵃ. ⵉ ⵓⵙⵎⴻⴽⵜⵉ, ⴰⵢⴰ bootcamp ⴷ ⴰⵢⴻⵏ ⴰⴽⴽ ⴷⴻⴳ ⵢⵉⵡⴻⵏ, ⴰⴷ ⵜⵍⴻⵎⴷⴻⴹ ⵢⴻⵔⵏⴰ ⴰⴷ ⵜⵃⴻⵎⵎⵍⴻⴹ ⵜⵓⵙ ...
ⵙ ⵢⵉⵙⴻⵎⵉⵡ ⴷ ⴰⵃⵔⵉⵛ ⵙⴻⴳ bootcamp ⵏ ⵓⵙⵏⴻⴼⵍⵉ ⵏ ⵡⴻⴱ, ⵢⴻⵙⵙⴻⴼⴽ ⴰⴷ ⴷⵉⵏⵉⵖ ⴱⴻⵍⵍⵉ ⵢⴻⴼⴼⴻⵖⴷ ⵏⵏⵉⴳ ⵏ ⵡⴰⵢⴻⵏ ⵜⵜⵕⴰⴵⵓⵖ. Bootcampa ⴷ ⵜⵉⴷⴻⵜⵜ ⴷ ⴰⵢⴻⵏ ⵢⴻⵜⵜⴻⵎⵛⴰⴱⵉⵏ, ⴷ ⴰⵢⴻⵏ ⵢⴻⵙⵙⴻⵡⵀⴰⵎⴻⵏ, ⵢⴻⵔⵏⴰ ⴷ ⴰⵢⴻⵏ ⵢⴻⵙⵙⴻⵡⵀⴰⵎⴻⵏ. ⵍⵎⴻⴷⵖ ⴰⵟⴰⵙ ⵏ ⵜⵖⴰⵡⵙⵉⵡⵉⵏ ⵙ ⵍⵎⴻⵏⴷⴰⴷ ⵏ ⵢⵉⵎⴻⵙⵏⴰⵍⵍⵓⵏⴻⵏⵉⵡ ⴷ ⵢⴰⵍ ⵢⵉⵡⴻⵏ ⵉ ...
ⵉⵙⴻⵍⵎⴰⴷⴻⵏ ⴷ ⵉⵎⴻⵇⵇⵔⴰⵏⴻⵏ, ⵜⵜⵇⴰⴷⴰⵔⴻⵏ, ⵜⵜⵃⵓⵍⴼⵓⵏ ⵢⴻⵔⵏⴰ ⵜⵜⴼⴻⵔⵃⴻⵏ. ⴰⴽⴰⵍⴰ ⵏ ⵓⵙⴻⵍⵎⴻⴷ ⴷ ⴰⵢⴻⵏ ⵉⴳⴻⵔⵔⵣⴻⵏ ⵢⴻⵔⵏⴰ ⴷ ⴰⵢⴻⵏ ⵢⴻⵙⵙⴻⵡⵀⴰⵎⴻⵏ, ⵜⴻⵙⵄⵉⴹ ⴰⵎⴽⴰⵏ ⴰⴽⴽⴻⵏ ⴰⴷ ⴷⵜⴻⵙⵜⴻⵇⵙⵉⴹ ⵉⵙⴻⵇⵙⵉⵢⴻⵏⵉⴽ ⵢⴻⵔⵏⴰ ⴷⴰⵖⴻⵏ ⴰⴷ ⵜⵜⴻⴽⴽⵉⵍⴻⴹ. ⵎⴰⵛⴰ ⴰⵢⴻⵏ ⵢⴻⵙⵄⴰⵏ ⴰⵣⴰⵍ ⴰⴽⴽ ⴷ ⴰⴽⴽⴻⵏ ⵜⵜⵀⴻⵢⵢⵉⵏⴽ ⵉ ⵓⵎⴰⴹⴰⵍ ⵏ ⵜⵖⴰⵡⵙⵉ ...
Bootcamp ⵏ ⵜⵖⴻⵍⵍⵉⵙⵜ ⵜⴰⵍⵉⴽⵟⵔⵓⵏⴰⵏⵜ ⴰⵢⴷⴻⴳ ⵍⵍⵉⵖ ⴷⴻⴳ 2022 ⵢⴻⵙⵙⴻⵍⵎⴻⴷⵉⵢⵉⴷ ⵜⵉⴼⵔⴰⵜ ⴷ ⵜⵎⵓⵙⵙⵏⵉⵡⵉⵏ ⵏ ⵍⵍⵙⴰⵙ ⴰⵢ ⵢⴻⵜⵜⵡⴰⵃⴻⵜⵜⵎⴻⵏ ⴼⴻⵍⵍⵉ ⴰⴽⴽⴻⵏ ⴰⴷ ⵙⵇⴻⴷⵛⴻⵖ ⵛⵛⵖⴻⵍ ⴷⴻⴳ TI. ⴰⵙⴻⵍⵎⴰⴷⵉⵡ ⵢⴻⵍⵍⴰ ⵢⴻⵙⵄⴰ ⵜⴰⵎⵓⵙⵏⵉ, ⵢⴻⵙⵄⴰ ⵚⵚⴱⴻⵔ ⵢⴻⵔⵏⴰ ⵢⴻⵍⵍⴰ ⴷⵉⵎⴰ ⵢⴻⴱⵖⴰ ⴰⴷ ⵉⵄⵉⵡⴻⵏ. ⵙⴻⵏⴷ ⴰⴷ ⵜⴼⴰⴽⴽ ⵜⴻⵙⵏⴰⵡⵉⵜ ...
ⵍⵎⵉⵣⴰⵏ ⴳⴰⵔ ⵜⵉⵥⵔⵉ ⴷ ⵜⵎⴻⵥⵔⵉ ⴷ ⵡⵉⵏ ⵉⴽⴻⵎⵍⴻⵏ, ⴰⴷ ⵜⴻⵙⵄⵓⴹ ⵜⴰⴳⵏⵉⵜ ⴰⴷ ⵜⴻⵙⵇⴻⴷⵛⴻⴹ ⴰⵢⴻⵏ ⵉ ⵜⴻⵙⵍⴻⵎⴷⴻⴹ ⴷⴻⴳ ⵍⴻⵛⵖⴰⵍ ⵏ ⵓⵅⵅⴰⵎ ⴷ ⵢⵉⵙⴻⵏⴼⴰⵔⴻⵏ ⵏ ⵜⵉⴷⴻⵜ ⵉ ⴷⵜⵜⵇⴻⵔⵔⵉⴱⴻⵏ TA. ⵏⴻⴽⴽ ⵙⵙⵓⵜⵓⵔⴻⵖ bootcampagi ⵉ ⵢⴰⵍ ⵢⵉⵡⴻⵏ ⵢⴻⴱⵖⴰⵏ ⴰⴷ ⵢⴻⴱⴷⵓ ⵛⵛⵖⴻⵍⵉⵙ ⴷⴻⴳ Data Science.