Data Management and Analysis for Quantitative Data using Python

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Introduction

This comprehensive course will be your guide to learning how to use the power of Python to analyze big data, create beautiful visualizations, and use powerful machine learning algorithms. This course is designed for both beginners with basic programming experience or experienced developers looking to make the jump to Data Science and big data Analysis.

Duration

5 Days

Course Objective

• o  Research Design

• Python for Data Science and Machine
• Spark for Big Data Analysis
• Implement Machine Learning Algorithms
• Numbly for Numerical Data
• Pandas for Data Analysis
• Matplotlib for Python Plotting
• Seaborn for statistical plots
• Interactive dynamic visualizations
• SciKit-Learn for Machine Learning Tasks
• K-Means Clustering, Logistic Regression and Linear Regression
• Random Forest and Decision Trees
• Natural Language Processing and Spam Filters
• Neural Networks
• Support Vector Machines
• Research report writing

Who Should Attend?

This is a general course targeting participants with elementary knowledge of Statistics from Agriculture, Economics, Food Security and Livelihoods, Nutrition, Education, Medical or public health professionals among others who already have some statistical knowledge, but wish to be conversant with the concepts and applications of statistical modeling using Python

Course content

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