Self-paced course
Certification program
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By completing this final capstone project you will apply various Data Analytics skills and techniques that you have learned as part of the previous courses in the IBM Data Analyst Professional Certificate. You will assume the role of an Associate Data Analyst who has recently joined the organization and be presented with a business challenge that requires data analysis to be performed on real-world datasets.
You will perform the various tasks that professional data analysts do as part of their jobs, including: - Data collection from multiple sources - Data wrangling and data preparation - Exploratory data analysis - Statistical analysis and data mining - Data visualization with different charts and plots, and - Interactive dashboard creation.
The project will culminate with a presentation of your data analysis report for various stakeholders in the organization. The report will include an executive summary, your analysis, and a conclusion. You will be assessed on both your work for the various stages in the Data Analysis process, as well as the final deliverable.
As part of this project you will demonstrate your proficiency with using Jupyter Notebooks, SQL, Relational Databases (RDBMS), Business Intelligence (BI) tools like Cognos, and Python Libraries such as Pandas, Numpy, Scikit-learn, Scipy, Matplotlib, Seaborn and others.
This project is a great addition to your portfolio and an opportunity to showcase your Data Analytics skills to prospective employers.
this course was a very good opportunity to practice almost all the materials studied in this specialization.
taking the role of an associative data analyst was very helping
Amazing course
very helpful for those who needs to polish their skills and trying to landing their career in field of Data
A good beginner friendly course in data analysis. Using the jupyter notebook was easier than going over to some websites to open the same jupyter notebook.
1
Apply different techniques to collect and wrangle data
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Showcase your Data Analysis and Visualization skills
3
Create a data analysis report and a compelling presentation
4
Demonstrate proficiency with various Python Libraries
Learning outcomes
Post this credential on your LinkedIn profile, resume, or CV, and don’t forget to celebrate your achievement by sharing it across your social networks or mentioning it during your performance review