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1 Campus

Vienna

7 Courses

- R - Python - Linux command line tools - Code conventions and complexity

Course Details

Minimum Skill Level
No coding experience required

ML Pipeline Supervised algorithms Unsupervised algorithms Recommender engines Graph analytics, including SNA Deep learning Natural language processing Ensembling algorithms Online learning

SQL - relational databases, introduction to SQL code NoSQL - overview of most popular databases APIs - how to pull data from APIs, introduction to the topic Data wrangling Introduction to scraping

Introduction to Hadoop and MapReduce Spark Hive/Pig Basics to cloud computing (AWS)

Making a write-up Making a codebook Presentations - How to present the results

Basics of Math, including: - Linear Algebra - Probability - Statistics (Hypothesis testing, A/B testing) - Basic Optimization: Parameter optimizatio, stochastic gradient descent

Principles Exploratory data analysis Basic visualizations

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