Key takeaways of Data Science
• An overview of the shift to Data Science Platforms
• The 2 critical components of a Data Science platform
• Industries that are most likely to get disrupted and shift to Data Science
• Characteristics of firms that get left behind the Data Science wave
• Factors that push an industry towards Data Science
• A brief overview of aspects of platform architecture beyond Hadoop
• What's in it for you ? How can an individual intercept this massive new trend ?
What's common to the following ?
Japanese dating app
Sensored cows in Netherland Googles autonomous car
The world around is changing …
• How our health gets cared for ?
• How we learn ?
• How we fall in love ?
• How we do farming ?
• How we drive ?
They all have Data Science embedded in them
(an intimate fabric of our lives)
How did the following players disrupt the Marketplace ?
• Amazon Defeated Borders ( Books )
• Netflix Defeated Blockbuster ( Video )
• iTunes Defeated Tower records ( Music )
• Google defeated Yahoo ( Search ) – Page rank
Ability to “see” patterns FASTER than competition is key to SURVIVAL !!!
Industries disrupted by Data Science
• Telecom ( Infrastructure optimisation, Network security )
• Banking ( Customer sentiment, Multi channel analysis )
• Digital channel ( Consumer engagement, Recommendation engines )
• Automotive ( Autonomous cards, Fords OnStar )
• Health care (Wearables )
• Oil n Gas ( Operations optimisation )
• Retail ( Digitisation )
What factors are driving companies towards data science ?
• Competitive advantage in the market place ( get ahead fast using unique insights )
• Existential threat ( others are moving ahead fast and I need to catch up )
• Revenue enhancement ( Cross sell models, recommenders )
• Cost optimisation ( Operational efficiency )
Overview of Data Science Platform ?
• Store massive torrents of data
• Billions of events
• Petabytes of data
• Emphasis on how to handle data
• Sense patterns from data for competitive advantage
• Emphasis on seeing patterns
• Advanced visualisation
• Text mining
“By 2018, the United States alone could
face a shortage of 140,000 to 190,000
people with deep analytical skills as well
as 1.5 million managers and analytics
with the know-how to use the analysis
of big data to make effective decisions”
McKinsey & Company: Big Data: The next frontier for competition
What you would learn at the end of 4 weeks ?
15 Core Foundational Building Blocks for next generation job market
CASES OF ML
4 Week Data Science Boot camp
Week by week plan
Demystifying Data Science
Introduction to Machine learning techniques
Step by Step methodology for converting noise to signal
12 tools of a Data Scientist
Descriptive vs Prescriptive statistics
How to do EDA ( Exploratory Data Analysis ) –Univariate / Bivariate / Corrrelations
Advanced Visualisation techniques
Data Science Lab Session-2 : Hands on Univariate + Bivariate + Correlation Analytics
Data Science Lab Session-1 : Getting feet wet in Data Science tools
Introduction to segmentation and clustering techniques
Segmentation in Retail Industry
Segmentation in Telecom industry
Segmentation in Healthcare industry
How to present for maximising Segmentation Business Impact
Data Science Lab Session-3 : Hands on SEGMENTATION on live data
Demystifying Predictive Analytical Models ( PAM )
Predictive Analytical Models in Retail Industry
Predictive Analytical Models in Telecom industry
Predictive Analytical Models in Healthcare industry
Mapping Impact of Predictive models on Business Outcomes
Summary of Key Data Science concepts
Data Science Lab Session-4 : Hands on PREDICTIVE ANALYTICS on live data
END 2 END MACHINE LEARNING PROJECT on
Live data ( Telecom or Retail or Banking )
Good luck in hunting for patterns using Data Science
Parece que tem um bloqueador de anúncios ativo. Ao listar o SlideShare no seu bloqueador de anúncios, está a apoiar a nossa comunidade de criadores de conteúdo.
Atualizámos a nossa política de privacidade.
Atualizámos a nossa política de privacidade de modo a estarmos em conformidade com os regulamentos de privacidade em constante mutação a nível mundial e para lhe fornecer uma visão sobre as formas limitadas de utilização dos seus dados.
Pode ler os detalhes abaixo. Ao aceitar, está a concordar com a política de privacidade atualizada.