Data Science Basics Quiz

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Mayelana nalolu hlelo lokusebenza

I-Data Science Basics Quiz wuhlelo lokusebenza Lwezisekelo Zesayensi Yedatha oluklanyelwe ukusiza abafundi, abafundi, nezingcweti ukuqinisa ukuqonda kwabo imiqondo yesayensi yedatha ngokusebenzisa imibuzo yokukhetha okuningi (ama-MCQs). Lolu hlelo lokusebenza luhlinzeka ngendlela ehlelekile yokuzijwayeza izihloko ezibalulekile njengokuqoqwa kwedatha, ukuhlanzwa, izibalo, amathuba, ukufunda ngomshini, ukubona ngeso, idatha enkulu, nokuziphatha.

Kungakhathaliseki ukuthi ulungiselela izivivinyo, izingxoxo, noma ufuna nje ukuthuthukisa amakhono akho, uhlelo lokusebenza lwe-Data Science Basics Quiz lenza ukufunda kuhehe, kufinyeleleke, futhi kuphumelele.

🔹 Izici Eziyinhloko Zohlelo Lokusebenza Lwemibuzo Yesayensi Yedatha

Umkhuba osuselwe ku-MCQ wokufunda nokubukeza okungcono.

Ihlanganisa ukuqoqwa kwedatha, izibalo, i-ML, idatha enkulu, ukubona ngeso, izimiso zokuziphatha.

Ilungele abafundi, abaqalayo, ochwepheshe kanye nabafuna umsebenzi.

Uhlelo lokusebenza lwe-Data Science Basics olusebenziseka kalula futhi olungasindi.

📘 Izihloko Ezihlanganiswe Kumibuzo Eyisisekelo Yesayensi Yedatha
1. Isingeniso Sesayensi Yedatha

Incazelo – Inkambu yemikhakha ehlukene ekhipha imininingwane kudatha.

I-Lifecycle - Ukuqoqwa kwedatha, ukuhlanzwa, ukuhlaziya, nokubona ngeso lengqondo.

Izicelo - Ukunakekelwa kwezempilo, ezezimali, ubuchwepheshe, ucwaningo, ibhizinisi.

Izinhlobo Zedatha - Okuhlelekile, okungahlelekile, okulinganiselwe, ukusakazwa.

Amakhono Ayadingeka - Ukuhlela, izibalo, ukubona ngeso, ulwazi lwesizinda.

Izimiso zokuziphatha - Ubumfihlo, ubulungisa, ukuchema, ukusetshenziswa okunesibopho.

2. Ukuqoqwa Kwedatha Nemithombo

Idatha Eyisisekelo - Izinhlolovo, ukuhlola, ukubhekwa.

Idatha Yesibili - Imibiko, amasethi edatha kahulumeni, imithombo eshicilelwe.

Ama-API - Ukufinyelela okuhleliwe kudatha ye-inthanethi.

I-Web Scraping - Ukukhipha okuqukethwe kumawebhusayithi.

Imininingwane - SQL, NoSQL, isitoreji samafu.

Imithombo Yedatha Enkulu - Imithombo yezokuxhumana, i-IoT, izinhlelo zokuthengiselana.

3. Data Cleaning & Preprocessing

Ukuphatha Idatha Elahlekile - Ukufakwa, ukuhumusha, ukususwa.

Uguquko – Ukwejwayela, ukukala, okuguquguqukayo kombhalo wekhodi.

Ukutholwa Kwangaphandle - Ukuhlolwa kwezibalo, ukuhlanganisa, ukubona ngeso.

Ukuhlanganiswa Kwedatha - Ukuhlanganisa amadathasethi amaningi.

Ukunciphisa - Ukukhethwa kwesici, ukuncishiswa kobukhulu.

Ukuhlolwa Kwekhwalithi - Ukunemba, ukungaguquguquki, ukuphelela.

4. Ukuhlaziywa Kwedatha Yokuhlola (EDA)

Izibalo Ezichazayo - Okushoyo, ukuhluka, ukuchezuka okujwayelekile.

Ukubona ngeso lengqondo - Histograms, scatterplots, heatmaps.

Ukuxhumana - Ukuqonda ubudlelwano obuguquguqukayo.

Ukuhlaziywa Kokusabalalisa - Ukujwayelekile, ukutsheka, i-kurtosis.

I-Categorical Analysis - Izibalo zefrequency, iziza zebha.

Amathuluzi EDA – Pandas, Matplotlib, Seaborn, Plotly.

5. Izibalo Nokungenzeka Okuyisisekelo

Amathuba Okucabanga - Imicimbi, imiphumela, izindawo zesampula.

Okuguquguqukayo okungahleliwe - Okuhlukile vs okuqhubekayo.

Ukusabalalisa - Okujwayelekile, i-binomial, i-Poisson, i-exponential njll.

6. Izisekelo Zokufunda Ngomshini

Ukufunda Okugadiwe - Ukuqeqeshwa okunedatha enelebula.

Ukufunda Okungagadiwe - Ukuhlanganisa, ubukhulu njll.

7. Ukubukwa Kwedatha Nokuxhumana

Amashadi – Umugqa, ibha, uphaya, hlakaza.

Amadeshibhodi - Amathuluzi e-BI okubukwayo okusebenzisanayo.

Ukuxoxa Indaba - Imibono ecacile enezindaba ezihlelekile.

Amathuluzi – Ithebula, Power BI, Google Data Studio.

Python Libraries – Matplotlib, Seaborn.

8. Idatha Enkulu Namathuluzi

Izimpawu - Ivolumu, isivinini, ukuhlukahluka, ubuqiniso.

I-Hadoop Ecosystem – HDFS, MapReduce, Hive, Pig.

I-Apache Spark - Ikhompyutha esabalalisiwe, izibalo zesikhathi sangempela.

Ama-Cloud Platforms - AWS, Azure, Google Cloud.

Imininingwane - SQL vs NoSQL.

Ukusakaza Data - Kafka, Flink amapayipi.

9. Idatha Yokuziphatha Nokuphepha

Ubumfihlo Bedatha – Ukuvikela imininingwane yomuntu.

Ukuchema - Ukuvimbela amamodeli angalungile noma abandlululayo.

I-AI Ethics – Ukungafihli, ukuziphendulela, ukuzibophezela.

Ukuphepha - Ukubethela, ukufakazela ubuqiniso, ukulawula ukufinyelela.

🎯 Ubani Ongasebenzisa Imibuzo Eyisisekelo Yesayensi Yedatha?

Abafundi - Funda futhi ubuyekeze imiqondo yesayensi yedatha.

Abaqalayo - Yakha isisekelo kwizisekelo zesayensi yedatha.

Abafuna Ukuhlolwa Kokuncintisana - Lungiselela izivivinyo ze-IT ne-analytics.

Abafuna Umsebenzi - Prakthiza ama-MCQ ezingxoxo ngezindima zedatha.

Ochwepheshe - Vuselela imiqondo eyinhloko namathuluzi.

📥 Landa Imibuzo Eyisisekelo Yesayensi Yedatha manje bese uqala uhambo lwakho lwesayensi yedatha namuhla!