4 Weeks Data Science Training in Bay area | Introduction to Data Science for beginners | Getting started with Data Science | What is Data Science? Why Data Science? Data Science Training | April 6, 2020 - April 29, 2020

4 WEEKS DATA SCIENCE TRAINING is being delivered as Instructor-led, guided TRAINING WITH REAL-life, Practical Hands-On Lab exercises from APRIL 6, 2020 - APRIL 29, 2020 for 16 hours over  4 weeks, 8 sessions, 2 sessions per week, 2 hours per session. * All Published Ticket Prices are in US Dollars * This course will be taught in English 4 WEEKS Data Science TRAINING SCHEDULE * April 6 - April 29 , 2020 US Pacific time * 4 Weeks | Monday, Wednesday every week US Pacific Time * 6:30 PM - 8:30 PM US Pacific time each of those days * Please click here to add your location and find your local date and time for the 1st Session [https://www.timeanddate.com/worldclock/converter.html?iso=20200407T013000&p1=234] FEATURES AND BENEFITS * 4 weeks, 8 sessions, 16 hours of total Instructor-led and guided, Practical Hands-On training * Training material, instructor handouts and access to useful resources on the cloud provided * Practical Hands-on Lab exercises provided * Actual code and scripts provided * Real-life Scenarios Data Science Training Course Pre-requisite Skills It is not required but preferred that you have some basic understanding of: * Mathematics * Statistics * Any Programming Language   Who should take this this Course? * Any IT Professional interested in enhancing or building their career in in the field of Data Science or becoming Data Scientist. * Any Working Professional. * Data Science Enthusiasts.   Data Science Training Course Objectives After completion of the Data Science Course, you will have the following knowledge: * 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  Data Science Training Course Outline * Introduction to Data Science * Data Science Deep Dive * Data Manipulation * Data Import Techniques * Exploratory Data Analysis * Data Visualization * Statistics * Statistics basics * Introduction to Machine Learning * Understanding Supervised and Unsupervised Learning Techniques * Clustering * Implementing Association rule mining * Understanding Process flow of Supervised Learning Techniques * Decision Tree Classifier * Random Forest Classifier * What is Random Forests * Naive Bayes Classifier. * Problem Statement and Analysis * Linear Regression * Logistic Regression * Text Mining * Sentimental Analysis * Support Vector Machines * Deep Learning * Time Series Analysis * Data Preprocessing * Linear And Logistic Regression Models. * K-means and Hierarchical Clustering. * Natural Language Processing. * Artificial Neural Networks. * Convolutional Neural Network.