This Data Science training is the top-rated course endorsed by Career Karma. It is designed to help you master the concepts of Data Science and gain valuable industry-relevant skills. With over 25 projects from various domains, this course ensures a hands-on and comprehensive learning experience.
Capstone Project:
The course includes dedicated mentor classes for you to create a high-quality industry project, solving a real-world problem using the skills and technologies learned throughout the course. The capstone project covers all the essential aspects of data extraction, cleaning, visualization, and building and tuning data models. You have the flexibility to choose the domain or industry dataset you want to work on from the available options.
Upon successfully completing and submitting the project, you will receive a capstone certificate for Data Science. This certificate can be a valuable asset to showcase your practical skills and knowledge to potential employers.
Course End Projects:
In addition to the capstone project, you will also have the opportunity to work on course-end projects that simulate real-world business problems. These projects are designed to help you apply the concepts learned in each specific course module. Typically, these projects take around 3-4 hours to complete.
Here are some examples of the course end projects:
Building a User-Based Recommendation Model for Amazon
Domain: E-commerce
In this project, you will perform data analysis on a dataset containing movie reviews by Amazon customers. Using machine learning algorithms, you will build a recommendation system that provides ratings for each user.
Comcast Telecom Customer Complaints
Domain: Telecommunications
In this project, you will utilize the existing database of customer complaints to improve customer satisfaction for Comcast, an American global telecommunication company. By analyzing the complaints data, you can identify areas for improvement and implement strategies to enhance customer experience.
Mercedes-Benz Greener Manufacturing
Domain: Automobile
This project aims to reduce the time a Mercedes-Benz spends on the test bench. By working with a dataset representing different permutations of car features, you will build predictive models to estimate the time required for testing. Optimal algorithms will contribute to faster testing and lower carbon dioxide emissions without compromising Mercedes-Benz’s standards.
Retail Analysis with Walmart
Domain: Retail
Walmart, one of the leading retail stores in the US, wants to accurately predict sales and demand. In this project, you will build a machine learning algorithm that incorporates various factors such as economic conditions, CPI, and unemployment index to predict sales. The goal is to help Walmart avoid stock shortages and meet customer demands effectively.
Movie Lens Case Study
Domain: Entertainment
Using exploratory data analysis techniques, you will perform an analysis to identify features that significantly affect the ratings of movies. Based on these findings, you will build a model that predicts movie ratings.
Customer Service Requests Analysis
Domain: Customer Service
In this project, you will analyze data on customer service requests made to New York City’s 311 service. By applying data wrangling techniques, you will uncover data patterns, create visualizations, and categorize and prioritize complaints based on factors such as economic conditions, CPI, and Unemployment Index.
Comparative Study of Countries
Domain: Geo-political
In this project, you will create a dashboard to compare various parameters of different countries using the sample insurance dataset and the world development indicators dataset. This analysis aims to provide insights into the socio-economic characteristics of different countries.
Sales Performance Analysis
Domain: Retail
The objective of this project is to build a dashboard that presents monthly sales performance by product segment and category. This will help clients identify the segments and categories that have met or exceeded their sales targets, as well as those that need improvement.
Predict the Demand for Loans based on the Region
Domain: Banking
In this project, you will gain insights into the banking sector by building a statistical model to predict the demand for loans in a specific region. Additionally, you will create an online dashboard that showcases the plan and its progress to all stakeholders.
Build a Model to Predict Diabetic Patients
Domain: Healthcare
Aligned with NIDDK (National Institute of Diabetes and Digestive and Kidney Diseases) data sets, this project aims to build a model that can predict patients with diabetes. By utilizing the given data set, you will develop a statistical model that can assist in identifying potential diabetic patients.
Customer Segmentation of Retail Customers
Domain: Retail
In this project, you will perform customer segmentation using RFM (Recency, Frequency, Monetary) analysis. By analyzing customer purchase patterns and behavior, you can segment retail customers based on their value and tailor marketing strategies accordingly.
These projects represent just a sample of the diverse range of industry applications covered in the Data Science course. By working on these projects, you will gain hands-on experience and practical skills that are highly valuable in the field of Data Science.
Enroll in the top-ranked Data Science course by Career Karma and take your data skills to the next level!
