Machine-Learning Intermediate Premium

Predictive Analytics Virtual Internship

In this 12-week virtual internship, students will learn to develop and deploy predictive models using machine learning techniques to forecast trends and make data-driven decisions. They will gain hands-on experience in data preprocessing, feature engineering, model selection, and model deployment, working with real-world datasets and industry-standard tools. By the end of the internship, students will have a portfolio of projects demonstrating their ability to leverage predictive analytics for business insights and strategic decision-making.

weeks
7 tasks
0 enrolled
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Track price: $49.00

Track Overview

This track provides hands-on experience and real-world projects to build your skills.

Tasks & Milestones

Data Cleaning and Transformation

Intermediate

In this task, students will clean and transform a real-world dataset, handling missing values and encoding categorical variables.

8 hours

Exploratory Data Analysis

Intermediate

In this task, students will perform exploratory data analysis to gain insights into the dataset and identify potential predictors.

6 hours

Regression Model Development

Intermediate

In this task, students will develop a regression model to predict a continuous target variable.

10 hours

Classification Model Development

Intermediate

In this task, students will develop a classification model to predict a categorical target variable.

10 hours

Model Packaging and Deployment

Intermediate

In this task, students will package their predictive models for deployment and integrate them into a simulated production environment.

8 hours

Model Monitoring and Governance

Intermediate

In this task, students will implement monitoring and logging mechanisms to track the performance of their deployed predictive models.

8 hours

Capstone Project

Intermediate

In this task, students will apply their skills in predictive analytics to solve a real-world problem.

40 hours

Prerequisites

  • • Proficiency in Python programming
  • • Familiarity with data manipulation and analysis libraries (e.g., NumPy, Pandas)

Certificate

Certificate of Completion

Earn a certificate upon successful completion