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Manage episode 348545564 series 3104198
Indhold leveret af Dependent Variable. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af Dependent Variable eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.
Catherine Gitau, Anthony Odhiambo & Victor Mochengo sat down for a casual conversation on what practical Data Science looks like in Kenya. This episode is for anyone interested in Data Science, works with data or is concerned with using Data as capital. Top 10 things we cover: 1) The buzzwords and jargons! Differentiate #datascience (DS), #machinelearning, #artificialintelligence, #bigdata etc 2)What companies are actively using hashtag#datascience in Kenya? 3)Are local companies DS ready? 4) How long should companies wait to expect reasonable return on their investment in DS? 5) Is there high demand for datascientists in Kenya? What does an ideal DS team look like? 6) Are data geeks well compensated in Kenya? 7) Conventional vs unconventional ways someone can get started? 8) What peer communities can Kenyan datascientists join? 9) What does a typical data science project look like? Challenges? 10) What interesting datascience projects have caught our eyes?
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9 episoder

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Manage episode 348545564 series 3104198
Indhold leveret af Dependent Variable. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af Dependent Variable eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.
Catherine Gitau, Anthony Odhiambo & Victor Mochengo sat down for a casual conversation on what practical Data Science looks like in Kenya. This episode is for anyone interested in Data Science, works with data or is concerned with using Data as capital. Top 10 things we cover: 1) The buzzwords and jargons! Differentiate #datascience (DS), #machinelearning, #artificialintelligence, #bigdata etc 2)What companies are actively using hashtag#datascience in Kenya? 3)Are local companies DS ready? 4) How long should companies wait to expect reasonable return on their investment in DS? 5) Is there high demand for datascientists in Kenya? What does an ideal DS team look like? 6) Are data geeks well compensated in Kenya? 7) Conventional vs unconventional ways someone can get started? 8) What peer communities can Kenyan datascientists join? 9) What does a typical data science project look like? Challenges? 10) What interesting datascience projects have caught our eyes?
  continue reading

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