- Sat, Feb 24, 2018 07:00 PM
Latitude: 50.0379, Longitude: 8.56215
Features & Benefits 8 sessions, each session of 2 hours spread over 4 weeks 16 hours of LIVE Instruction spread over 4 weeks Training material with lab exercises provided Each session is recorded and recordings are provided to students over Microsoft Cloud Course dates: February 24 - Marchl 18, 2018 Weekly Schedule Saturday and Sunday, every week 8:00 AM - 10:00 AM (US Pacific Standard Time) each day Please confirm your local time Video Conference Link Will be sent upon registration and payment Training Provider: Omni212 Omni212 IT Training https://www.omni212.com/services/training/ Course Overview This Data Science course will help you gain expertise in Machine Learning Algorithms like K-Means Clustering, Decision Trees, Random Forest, Naive Bayes using R. You'll learn the concepts of Statistics, Time Series, Text Mining and an introduction to Deep Learning. You'll solve real life case studies on Media, Healthcare, Social Media, Aviation, HR. About this course In this data science course, you will learn key concepts in data acquisition, preparation, exploration, and visualization taught alongside practical application oriented examples such as how to build a cloud data science solution using Machine Learning platform, or with R, and Python on Azure stack. What you will learn in this course? Explore the data science process Probability and statistics in data science Data exploration and visualization Data ingestion, cleansing, and transformation Introduction to machine learning The hands-on elements of this course leverage a combination of R, Python, and Machine Learning What are the prerequisites? Python programming knowledge Basic machine learning knowledge (especially supervised learning) Basic statistics knowledge (mean, variance, standard deviation, etc.) Linear algebra (vectors, matrices, etc.) Calculus (differentiation, integration, partial derivatives, etc.) Course Outline Data Preprocessing Linear And Logistic Regression Models. Decision Trees and Random Forest. Naive Bayes and Support Vector Machine. K-means and Hierarchical Clustering. Natural Language Processing. Artificial Neural Networks. Convolutional Neural Network. Refund Policy 1. There are no refunds.2. If for any reason the course has not been taken, class is cancelled or rescheduled, the payment can be applied towards any future course by Omni212.