BEGIN:VCALENDAR VERSION:2.0 PRODID:-//Opus Kinetic - ECPv6.15.12.2//NONSGML v1.0//EN CALSCALE:GREGORIAN METHOD:PUBLISH X-ORIGINAL-URL:https://www.opuskinetic.com X-WR-CALDESC:Events for Opus Kinetic REFRESH-INTERVAL;VALUE=DURATION:PT1H X-Robots-Tag:noindex X-PUBLISHED-TTL:PT1H BEGIN:VTIMEZONE TZID:Asia/Singapore BEGIN:STANDARD TZOFFSETFROM:+0800 TZOFFSETTO:+0800 TZNAME:+08 DTSTART:20250101T000000 END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTART;VALUE=DATE:20260511 DTEND;VALUE=DATE:20260515 DTSTAMP:20260405T112641 CREATED:20240807T072507Z LAST-MODIFIED:20260309T032018Z UID:10002422-1778490000-1778778000@www.opuskinetic.com SUMMARY:Practical Data Science and Machine Learning for Oil & Gas Professionals DESCRIPTION:Why Choose this Training Course\nThis highly practical data science training course is designed to equip Oil & Gas professionals with a thorough introduction to essential machinlearning methods and a solid hands-on experience in data science and machine learning applications. \nThroughout this data science training\, participants will acquire comprehensive knowledge and develop practical skills necessary for integrating data science and machine learning into their daily work. By mastering these techniques\, participants will improve efficiency and effectiveness in both current and future projects\, ultimately leading to significant improvements in overall performance and substantial value creation for their companies. \nWho Should Attend\nGeologists\, petrophysicists\, reservoir engineers\, production engineers\, drilling engineers and other Oil & Gas professionals keen to obtain a fundamental understanding and practical skills in Machine Learning and Data Science. \nPrerequisite: \n\nParticipants should have strong upstream domain knowledge and at least 5 years of experience.\nPrior programming experience (Python) is an advantage. Recommended pre-reading material on Python can be provided upon request.\n\nKey Learning Objectives\n\nComprehensive Introduction: Gain a foundational understanding of both supervised and unsupervised learning algorithms\, including advanced topics such as deep learning and model explainability.\nHands-On Experience: Build practical skills through detailed\, step-by-step guidance on applying various machine learning methods to real-world Oil & Gas problems.\nConfidence Building: Start with simple\, clear explanations of each method\, gradually progressing to more complex applications and techniques.\nCapability enhancement: Learn how to implement the knowledge gained\, using carefully crafted code examples that can be directly applied to ongoing and future projects\, enhancing overall performance.\nBusiness impact assessment: Develop the ability to identify actual Oil & Gas industry challenges and solve them\neffectively by leveraging Machine Learning and Data Science methods.\n\nEnquiry Form\n\n\n \n \n SalutationMr.Ms.Miss.Mrs.Mdm.Dr.Prof.Capt.-Name*\n \n \n \n First\n \n \n \n \n Last\n \n \n Phone*Email*\n \n Company*Current Location* \n \n \n AfghanistanAlbaniaAlgeriaAmerican SamoaAndorraAngolaAnguillaAntarcticaAntigua and BarbudaArgentinaArmeniaArubaAustraliaAustriaAzerbaijanBahamasBahrainBangladeshBarbadosBelarusBelgiumBelizeBeninBermudaBhutanBoliviaBonaire\, Sint Eustatius and SabaBosnia and HerzegovinaBotswanaBouvet IslandBrazilBritish Indian Ocean TerritoryBrunei DarussalamBulgariaBurkina FasoBurundiCambodiaCameroonCanadaCape VerdeCayman IslandsCentral African RepublicChadChileChinaChristmas IslandCocos IslandsColombiaComorosCongoCongo\, Democratic Republic of theCook IslandsCosta RicaCroatiaCubaCuraçaoCyprusCzechiaCôte d'IvoireDenmarkDjiboutiDominicaDominican RepublicEcuadorEgyptEl SalvadorEquatorial GuineaEritreaEstoniaEswatiniEthiopiaFalkland IslandsFaroe IslandsFijiFinlandFranceFrench GuianaFrench PolynesiaFrench Southern TerritoriesGabonGambiaGeorgiaGermanyGhanaGibraltarGreeceGreenlandGrenadaGuadeloupeGuamGuatemalaGuernseyGuineaGuinea-BissauGuyanaHaitiHeard Island and McDonald IslandsHoly SeeHondurasHong KongHungaryIcelandIndiaIndonesiaIranIraqIrelandIsle of ManIsraelItalyJamaicaJapanJerseyJordanKazakhstanKenyaKiribatiKorea\, Democratic People's Republic ofKorea\, Republic ofKuwaitKyrgyzstanLao People's Democratic RepublicLatviaLebanonLesothoLiberiaLibyaLiechtensteinLithuaniaLuxembourgMacaoMadagascarMalawiMalaysiaMaldivesMaliMaltaMarshall IslandsMartiniqueMauritaniaMauritiusMayotteMexicoMicronesiaMoldovaMonacoMongoliaMontenegroMontserratMoroccoMozambiqueMyanmarNamibiaNauruNepalNetherlandsNew CaledoniaNew ZealandNicaraguaNigerNigeriaNiueNorfolk IslandNorth MacedoniaNorthern Mariana IslandsNorwayOmanPakistanPalauPalestine\, State ofPanamaPapua New GuineaParaguayPeruPhilippinesPitcairnPolandPortugalPuerto RicoQatarRomaniaRussian FederationRwandaRéunionSaint BarthélemySaint Helena\, Ascension and Tristan da CunhaSaint Kitts and NevisSaint LuciaSaint MartinSaint Pierre and MiquelonSaint Vincent and the GrenadinesSamoaSan MarinoSao Tome and PrincipeSaudi ArabiaSenegalSerbiaSeychellesSierra LeoneSingaporeSint MaartenSlovakiaSloveniaSolomon IslandsSomaliaSouth AfricaSouth Georgia and the South Sandwich IslandsSouth SudanSpainSri LankaSudanSurinameSvalbard and Jan MayenSwedenSwitzerlandSyria Arab RepublicTaiwanTajikistanTanzania\, the United Republic ofThailandTimor-LesteTogoTokelauTongaTrinidad and TobagoTunisiaTurkmenistanTurks and Caicos IslandsTuvaluTürkiyeUS Minor Outlying IslandsUgandaUkraineUnited Arab EmiratesUnited KingdomUnited StatesUruguayUzbekistanVanuatuVenezuelaViet NamVirgin Islands\, BritishVirgin Islands\, U.S.Wallis and FutunaWestern SaharaYemenZambiaZimbabweÅland Islands\n Country\n \n \n How many people are you looking at?1 - 2 Standard Rates3 - 5 Group Discount>10 In-House Training\, Huge Savings!Undecided\, need more informationThis is just an approximate number. You can finalise it when you send in the registration form.\n \n Send me brochure\n Comments:CAPTCHA URL:https://www.opuskinetic.com/training/data-science-training-2/2026-05-11/ LOCATION:Kuala Lumpur\, Federal Territory of Kuala Lumpur\, Kuala Lumpur\, Malaysia CATEGORIES:Big Data, AI & Cybersecurity,Geology,Reservoir Engineering ATTACH;FMTTYPE=image/jpeg:https://www.opuskinetic.com/wp-content/uploads/2021/11/machine-learning-fi1-scaled.jpg ORGANIZER;CN="Opus Kinetic Pte Ltd":MAILTO:info@opuskinetic.com GEO:3.1384965;101.7099933 END:VEVENT BEGIN:VEVENT DTSTART;VALUE=DATE:20260713 DTEND;VALUE=DATE:20260717 DTSTAMP:20260405T112641 CREATED:20240807T072507Z LAST-MODIFIED:20260309T032018Z UID:10002421-1783933200-1784221200@www.opuskinetic.com SUMMARY:Practical Data Science and Machine Learning for Oil & Gas Professionals DESCRIPTION:Why Choose this Training Course\nThis highly practical data science training course is designed to equip Oil & Gas professionals with a thorough introduction to essential machinlearning methods and a solid hands-on experience in data science and machine learning applications. \nThroughout this data science training\, participants will acquire comprehensive knowledge and develop practical skills necessary for integrating data science and machine learning into their daily work. By mastering these techniques\, participants will improve efficiency and effectiveness in both current and future projects\, ultimately leading to significant improvements in overall performance and substantial value creation for their companies. \nWho Should Attend\nGeologists\, petrophysicists\, reservoir engineers\, production engineers\, drilling engineers and other Oil & Gas professionals keen to obtain a fundamental understanding and practical skills in Machine Learning and Data Science. \nPrerequisite: \n\nParticipants should have strong upstream domain knowledge and at least 5 years of experience.\nPrior programming experience (Python) is an advantage. Recommended pre-reading material on Python can be provided upon request.\n\nKey Learning Objectives\n\nComprehensive Introduction: Gain a foundational understanding of both supervised and unsupervised learning algorithms\, including advanced topics such as deep learning and model explainability.\nHands-On Experience: Build practical skills through detailed\, step-by-step guidance on applying various machine learning methods to real-world Oil & Gas problems.\nConfidence Building: Start with simple\, clear explanations of each method\, gradually progressing to more complex applications and techniques.\nCapability enhancement: Learn how to implement the knowledge gained\, using carefully crafted code examples that can be directly applied to ongoing and future projects\, enhancing overall performance.\nBusiness impact assessment: Develop the ability to identify actual Oil & Gas industry challenges and solve them\neffectively by leveraging Machine Learning and Data Science methods.\n\nEnquiry Form\n\n \n \n SalutationMr.Ms.Miss.Mrs.Mdm.Dr.Prof.Capt.-Name*\n \n \n \n First\n \n \n \n \n Last\n \n \n Phone*Email*\n \n Company*Current Location* \n \n \n AfghanistanAlbaniaAlgeriaAmerican SamoaAndorraAngolaAnguillaAntarcticaAntigua and BarbudaArgentinaArmeniaArubaAustraliaAustriaAzerbaijanBahamasBahrainBangladeshBarbadosBelarusBelgiumBelizeBeninBermudaBhutanBoliviaBonaire\, Sint Eustatius and SabaBosnia and HerzegovinaBotswanaBouvet IslandBrazilBritish Indian Ocean TerritoryBrunei DarussalamBulgariaBurkina FasoBurundiCambodiaCameroonCanadaCape VerdeCayman IslandsCentral African RepublicChadChileChinaChristmas IslandCocos IslandsColombiaComorosCongoCongo\, Democratic Republic of theCook IslandsCosta RicaCroatiaCubaCuraçaoCyprusCzechiaCôte d'IvoireDenmarkDjiboutiDominicaDominican RepublicEcuadorEgyptEl SalvadorEquatorial GuineaEritreaEstoniaEswatiniEthiopiaFalkland IslandsFaroe IslandsFijiFinlandFranceFrench GuianaFrench PolynesiaFrench Southern TerritoriesGabonGambiaGeorgiaGermanyGhanaGibraltarGreeceGreenlandGrenadaGuadeloupeGuamGuatemalaGuernseyGuineaGuinea-BissauGuyanaHaitiHeard Island and McDonald IslandsHoly SeeHondurasHong KongHungaryIcelandIndiaIndonesiaIranIraqIrelandIsle of ManIsraelItalyJamaicaJapanJerseyJordanKazakhstanKenyaKiribatiKorea\, Democratic People's Republic ofKorea\, Republic ofKuwaitKyrgyzstanLao People's Democratic RepublicLatviaLebanonLesothoLiberiaLibyaLiechtensteinLithuaniaLuxembourgMacaoMadagascarMalawiMalaysiaMaldivesMaliMaltaMarshall IslandsMartiniqueMauritaniaMauritiusMayotteMexicoMicronesiaMoldovaMonacoMongoliaMontenegroMontserratMoroccoMozambiqueMyanmarNamibiaNauruNepalNetherlandsNew CaledoniaNew ZealandNicaraguaNigerNigeriaNiueNorfolk IslandNorth MacedoniaNorthern Mariana IslandsNorwayOmanPakistanPalauPalestine\, State ofPanamaPapua New GuineaParaguayPeruPhilippinesPitcairnPolandPortugalPuerto RicoQatarRomaniaRussian FederationRwandaRéunionSaint BarthélemySaint Helena\, Ascension and Tristan da CunhaSaint Kitts and NevisSaint LuciaSaint MartinSaint Pierre and MiquelonSaint Vincent and the GrenadinesSamoaSan MarinoSao Tome and PrincipeSaudi ArabiaSenegalSerbiaSeychellesSierra LeoneSingaporeSint MaartenSlovakiaSloveniaSolomon IslandsSomaliaSouth AfricaSouth Georgia and the South Sandwich IslandsSouth SudanSpainSri LankaSudanSurinameSvalbard and Jan MayenSwedenSwitzerlandSyria Arab RepublicTaiwanTajikistanTanzania\, the United Republic ofThailandTimor-LesteTogoTokelauTongaTrinidad and TobagoTunisiaTurkmenistanTurks and Caicos IslandsTuvaluTürkiyeUS Minor Outlying IslandsUgandaUkraineUnited Arab EmiratesUnited KingdomUnited StatesUruguayUzbekistanVanuatuVenezuelaViet NamVirgin Islands\, BritishVirgin Islands\, U.S.Wallis and FutunaWestern SaharaYemenZambiaZimbabweÅland Islands\n Country\n \n \n How many people are you looking at?1 - 2 Standard Rates3 - 5 Group Discount>10 In-House Training\, Huge Savings!Undecided\, need more informationThis is just an approximate number. You can finalise it when you send in the registration form.\n \n Send me brochure\n Comments:CAPTCHA URL:https://www.opuskinetic.com/training/data-science-training-2/2026-07-13/ LOCATION:Kuala Lumpur\, Federal Territory of Kuala Lumpur\, Kuala Lumpur\, Malaysia CATEGORIES:Big Data, AI & Cybersecurity,Geology,Reservoir Engineering ATTACH;FMTTYPE=image/jpeg:https://www.opuskinetic.com/wp-content/uploads/2021/11/machine-learning-fi1-scaled.jpg ORGANIZER;CN="Opus Kinetic Pte Ltd":MAILTO:info@opuskinetic.com GEO:3.1384965;101.7099933 END:VEVENT END:VCALENDAR