This is the final course in the IBM Data Science Professional Certificate as well as the Applied Data Science with Python Specialization. This capstone project course will give you the chance to practice the work that data scientists do in real life when working with datasets.

À propos de ce cours
This course requires working knowledge of Python programming, Data Analysis, Data Visualization, SQL, Model Development and Evaluation.
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Demonstrate proficiency in data science and machine learning techniques using a real-world data set and prepare a report for stakeholders
Apply your skills to perform data collection, data wrangling, exploratory data analysis, data visualization model development, and model evaluation
Write Python code to create machine learning models including support vector machines, decision tree classifiers, and k-nearest neighbors
Evaluate the results of machine learning models for predictive analysis, compare their strengths and weaknesses and identify the optimal model
Compétences que vous acquerrez
- Methodology
- Github
- Jupyter Notebook
- Data Science Methodology
- K-Means Clustering
This course requires working knowledge of Python programming, Data Analysis, Data Visualization, SQL, Model Development and Evaluation.
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Programme de cours : ce que vous apprendrez dans ce cours
Introduction
Exploratory Data Analysis (EDA)
Interactive Visual Analytics and Dashboard
Predictive Analysis (Classification)
Avis
- 5 stars80,27 %
- 4 stars14,15 %
- 3 stars3,12 %
- 2 stars1,10 %
- 1 star1,35 %
Meilleurs avis pour APPLIED DATA SCIENCE CAPSTONE
It was a long marathon for me, it lasted about 6.5 months. It was a useful and well-prepared course. I would like to thank all the instructors one by one. Thanks to IBM and Coursera.
Its was great experience in completing the project using all skills that we learned in the course, thanks to coursera and IBM for giving me an opportunity to update my selft and also to test my skills
Very challenging but truly rewarding. I learnt a lot through the mistakes I made throughout the project but there is a lot of support on the forum and the internet to help with any issue.
This is a great course and lots of fun. But it is a big commitment and you need to take it seriously. To get the most out of this course you will need to spend at least 30 hours doing it.
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