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Inference, • data gathering, • business optimization, by combining some of those processes above. Data Industry 2013 - 2014 Job - Quant, - Data Scientist, - ML Engineer - Marketing Analytics, - Social Researcher, - "Bigdata" analyst, - Social Media analyst, - Experimenter - Business Intelligence Analyst - Many more
Analytics” in Indonesia. • Something similar was developed at that time, Social Media Analysis. • There was a social media usage boom at that time. People love to use social media. • Company want to cater their marketing according to people’s social media behavior. Data Industry 2013 - 2014 Social Media Analysis • Sentiment Analysis • Cluster in Twitter networks • User profiling untuk Marketing
Media Researcher • Statistician It’s a wrong generalization, but it can capture common pattern of job at that time. Skills Needed • R • SPSS • Statistics Barrier to Entry • Low Data Industry 2013 - 2014
data from social media, say 10TB • It need to be stored and processed in a large scale. • People came up with “Big Data Solution” • It is a jargon • In 2014, the increase of social media usage was still huge. • Twitter gave their data for free, but limited. • No privacy issue/problem • People make many twitter bots to tackle that limitation. • Social Media Monitoring services increased in Indonesia
Engineering • Natural Language Processing Barrier to Entry • Medium Most Common Jobs in 2014 • BigData Engineer • Data Engineer • Social Media Researcher • Statistician Data Industry 2013 - 2014
People loved to talk about Machine Learning and AI. • But.. Machine Learning usage in industry was very rare. • Some of the prominent startups was hiring Data Scientist, e.g. Bukalapak and Traveloka Data Industry 2015 - 2016 Data Scientist • People without any skills and experience were claiming to be a Data Scientist. • No ML skills • No Statistics skills • Never deploy any ML services
Deep Learning boom! • People loved to talk about Deep Learning • But.. Deep Learning usage in industry was very rare. • Nonetheless industry became more technical. Deep Learning • People still don’t know how to install Tensorflow with CUDA • They didn’t understand Deep Learning • But.. they have understand Machine Learning in general • Never deploy any ML services Data Industry 2015 - 2016
to Entry • High • Salary increased • Portfolio • Hacker rank…. Most Common Jobs in 2016 • Data Scientist ◦ Data Scientist became a hot career! • Data Engineer Data Industry 2015 - 2016
ML dan DL. • Some startups already deployed their first ML services and have great success, e.g Salestock and Kata.ai • There was a huge increase in Data Scientist Supply • Most of these DS don’t understand Math, Stats, ML, and “deployment skills”. “Data Scientist” Data Industry 2017 - 2018
Statistics • Deployment, some SoftEng skills Barrier to Entry • Higher! • Salary increased • Portfolio • Hacker rank…. Most Common Jobs in 2017 • Data Scientist ◦ Data Scientist became a hot career! • Data Engineer • ML Engineer Data Industry 2017 - 2018
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Python Data Wrangling Visualization Probability I Sampling Probability II Calculus II: Multivariable Calculus Abtest AbtestProj Questionnaire Design Questionnaire Project Applied Linear Algebra Econometrics Applied Linear Model Cases Time Series Causality Optimization
Python Data Wrangling Visualization DataBase Probability I Probability II Calculus II: Multivariable Calculus Applied Linear Algebra Introduction to Machine Learning Machine Learning Cases DevTools Econometrics Applied Linear Model Cases Time Series Causality Optimization Deep Learning