Predictive Analytics for Sales Forecasting Virtual Internship
In this 12-week virtual internship, students will learn how to leverage data mining and machine learning techniques to build predictive models for sales forecasting and pipeline management. They will gain hands-on experience in data preprocessing, feature engineering, model selection, and performance evaluation to deliver accurate and insightful sales forecasts. By the end of the internship, students will be equipped with the skills to drive data-driven decision-making and optimize sales strategies for businesses.
Track Overview
Tasks & Milestones
Data Exploration and Preprocessing
IntermediateIn this task, students will explore and preprocess sales data from various sources to prepare it for modeling.
Univariate and Bivariate Analysis
IntermediateIn this task, students will conduct univariate and bivariate analysis on the sales data to understand the distribution, trends, and relationships between variables.
Feature Engineering and Selection
IntermediateIn this task, students will explore and engineer new features from the sales data to improve the predictive power of their models.
Model Development and Evaluation
IntermediateIn this task, students will develop and evaluate multiple predictive models for sales forecasting using various machine learning algorithms.
Sales Pipeline Management
IntermediateIn this task, students will explore how the selected sales forecasting model can be applied to pipeline management and optimization.
Dashboard Development and Presentation
IntermediateIn this task, students will create a dashboard to visualize the sales forecasting insights and present their findings to a panel of stakeholders.
Prerequisites
- • Basic understanding of statistics and data analysis
- • Familiarity with programming languages such as Python or R
Certificate
Certificate of Completion
Earn a certificate upon successful completion