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Data Scientist Level 5: Data Science Capstone Project
With this Data Science Capstone project you will have an opportunity to implement the skills that you learned in this Program.
Here you will learn to solve a real-world, industry-aligned Data Science problem.
You will apply the steps such as data processing, model building, reporting your business results and insights.
This project is the final step in the learning path and it will enable you to showcase your expertise in the field of Data Science.
Course Outlines
- Data science project problem statement.
- Complete data science life-cycle steps.
- Presenting and sharing the results.
What you'll learn
- This Data Science Capstone course will give you an overview of Data Science decision life cycle which includes data processing, building the model, representing results and improving the model performance.
- In this course you will learn,
- Data Processing – Apply data processing techniques to make the raw data meaningful.
- Model Building – Use regression, classification and clustering algorithms to build Machine Learning models and make predictions.
- Here you will follow the complete data science lifecycle which includes steps such as data processing, Model building and trining, k-fold crossvalidation process and model tuning.
- Model Fine-tuning – Applying various techniques to improve the accuracy and selecting the best model on the basis of accuracy.
- Dashboarding and Representing Results – This is the last step, here you will export the results into a dashboard with meaningful insights using Tableau.
Course Content
- This Data Science Capstone course will give you an overview of Data Science decision life cycle which includes data processing, building the model, representing results and improving the model performance.
- In this course you will learn,
- Data Processing – Apply data processing techniques to make the raw data meaningful.
- Model Building – Use regression, classification and clustering algorithms to build Machine Learning models and make predictions.
- Here you will follow the complete data science lifecycle which includes steps such as data processing, Model building and trining, k-fold crossvalidation process and model tuning.
- Model Fine-tuning – Applying various techniques to improve the accuracy and selecting the best model on the basis of accuracy.
- Dashboarding and Representing Results – This is the last step, here you will export the results into a dashboard with meaningful insights using Tableau.
Customize a Course
We will be happy to assist you for inquiries about a customized scheduled or program:
Rachael McPherson, Director of Sales
☎(250)882-9549 📧rachael@qacademy.tech
Caroline Santos, Corporate and Custom Sales Manager- Eastern Canada
☎(514)771-3206 📧caroline.santos@qacademy.tech
Course Info
- (514)771-3206
- caroline.santos@qacademy.tech
