land the machine learning job you want

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Outco’s new Machine Learning Program is accepting applications for the July 13th cohort.

Apply to join this motivated group of ML practitioners who are ready to level up their careers.

everything you need to land a great ML job

Week 0: Understanding the Job Search and Statistical Machine Learning

  • Breaking down the white boarding process (data structures and algorithms)

  • Statistical classification, linear algebra, regression, information theory, Markov, and Bayesian models

  • Interviewing perspectives, recognizing your value, structured communication techniques

Week 1: Recursion and Dynamic Programming Paradigms

  • Recursive algorithms — how to construct and solve them

  • Dynamic programming techniques (tabulation and memoization)

  • Sliding window algorithm problems

Week 2: Machine Learning for Data Science

  • Data Modeling (Regressions, Decision Trees, Random Forests)

  • Clustering (kMeans, Feature Clusters, Gradient Boosting)

  • Applying advanced forms of support vector machines, such as random forests, and maximum margin.

Week 3: Applied Machine Learning Infrastructure

  • Cleaning data for optimal ML processing pipelines

  • Building common software pipelines for ML

  • How to build recommender systems and Anomaly Detection 

  • Designing alternate streaming processes for big-data ML

Week 4: Neural Networks and Reinforcement Learning

  • Building Deep, Convolutional Neural Networks for Visual Recognition

  • Learning about Applied Reinforcement Learning (Value Based Methods, Policy Based, Multi-Agent)

  • Creating Neural Networks for natural language processing

After Week 4, participants have lifetime access to curriculum and career support.

Meet your instructor

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Sean Batir’s professional experience lies at the intersection of artificial intelligence, software engineering, and biotechnology, with over a decade of experience working with neural systems. Sean currently works at BMW’s research division developing software that enables artificial intelligence.

He graduated from the Massachusetts Institute of Technology with a Bachelor of Science in Brain and Cognitive Sciences and completed study at the Imperial College of London, with a Master’s of Research in Bioengineering with a specialization in neural processing algorithms. At the University of Oxford Said Business School, he earned a Certificate in Entrepreneurship and Innovation for Biotechnology and he’s currently on a leave from a Ph.D. for Theoretical Neuroscience at Columbia University.

His work focuses on the interdisciplinary crossroads of IoT, AI, and swarm intelligence and he’s helped submit over a dozen patents, and co-founded two startups.


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