Hamoye_Data_Science_Internship

Data Science

The data science track includes multiple carefully crafted courses. These include

1. Introduction to Python for Machine Learning, Regression in Machine Learning, Classification in Machine Learning, Neural Networks, Image Recognition, and Object Detection, Practical Time Series Analysis, and a capstone project.

Stage A

• Introduction To Python For Machine Learning

• The Complete Data Science Pipeline

• Introduction to NumPy & Creating Arrays

• Pandas

• Project

Stage B

• Simple Linear Regression

• Multiple Linear Regression

• Penalization Methods

• Non Linear Regression

• Project

Premier Project Phase

• List Of Projects

• Team XGBoost

  • Topic: Football Events Analysis

  • Project Description

  • A football game generates many more events and it is very important and interesting to take into account the context in which those events were generated. This dataset should keep sports analytics enthusiasts awake for long hours as the number of questions that can be asked is huge.

• Project - Football Events Analysis

• Data Set

Stage C

Machine Learning: Classification - Managing the Quality Metric of Global Ecological Footprint

• Linear Classification and Logistic Regression
• Measuring_Classification_Performance *
• Multiclass_Classification
• Tree-Based Methods and The Support Vector Machine
• Ensemble_Methods
• Project
• Premier Project(Football Events)

Stage D

Neural Network, Image Recognition & Object Detection

• Introduction to Artificial Neural Network & the Keras Framework

• Regularization and Optimisation

• Convolutional Neural Networks

• Introduction to Large Scale Image Recognition Architecture

• Object Detection - Multi-Object Classification plus Localization

• Project

Stage E

Practical Time Series Analysis & Forecast

• Basics of Time Series

• Wrangling Time Series Data

• Forecasting Performance Measures

• Time Series Forecasting Using Stochastic Models

• Time Series at Scale

• Projects

Industrial Technical Session

• Technical Session1

• Technical Session2

  • Session Video

• Cap Stone Project