capstone project examples

coursera ibm data analyst capstone project github 2

coursera ibm data analyst capstone project github 2

Data Science — ashna

Looking for help from course takers in IBM Specialization track.

Can someone help to review my capstone?

https://www.coursera.org/learn/ibm-cybersecurity-breach-case-studies/peer/VSq7Z/applied-project-investigate-a-recent-data-breach/review/XGxsR7wmEeq-Hg6S61FThw

Thanks in advance

Data Science

coursera ibm data analyst capstone project github 2

I stuck at capstone project on data breach. Would you be kind enough to review for me? https://www.coursera.org/learn/ibm-cybersecurity-breach-case-studies/peer/VSq7Z/applied-project-investigate-a-recent-data-breach/review/EZvMQB0PEeuAsA5_o4vabw

coursera ibm data analyst capstone project github 2

Manoj Kumar C R

Hey aashna i reviewed yours and can you help me in finishing the assessment so that we can do together

https://www.linkedin.com/in/manoj-kumar-c-r-b871311a9

Please connect to me over here

coursera ibm data analyst capstone project github 2

RohinReghunath

i’m also stuck at this please help https://www.coursera.org/learn/ibm-cybersecurity-breach-case-studies/peer/VSq7Z/applied-project-investigate-a-recent-data-breach/review/LUAZy_auEeueAg5VKClqKQ

coursera ibm data analyst capstone project github 2

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Capstone Project Notebook for the IBM Data Science Professional Certificate

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IBM Data Analyst Professional Certificate

Unlock your potential in data analytics. Build job-ready skills for an in-demand career as a data analyst. No degree or prior experience required.

Instructors: Rav Ahuja +8 more

Instructors

Financial aid available

133,302 already enrolled

Professional Certificate - 9 course series

(13,291 reviews)

Recommended experience

No degree or prior experience required. All you need is basic computer literacy, high school math, and comfort with numbers.

What you'll learn

Demonstrate proficiency in using spreadsheets and utilizing Excel to perform a variety of data analysis tasks like data wrangling and data mining

Create various charts and plots in Excel & work with IBM Cognos Analytics to build dashboards. Visualize data using Python libraries like Matplotlib

Develop working knowledge of Python language for analyzing data using Python libraries like Pandas and Numpy, and invoke APIs and Web Services

Describe data ecosystem and Compose queries to access data in cloud databases using SQL and Python from Jupyter notebooks

Skills you'll gain

Details to know

coursera ibm data analyst capstone project github 2

Add to your LinkedIn profile

Available in English

Subtitles: English, Arabic, French, Portuguese (European), Italian, Vietnamese, German, Russian, Turkish, Spanish, Persian, Korean

See how employees at top companies are mastering in-demand skills

Prepare for a career in Data Analytics

Get exclusive access to career resources upon completion

Get free access to IBM’s People and Soft Skills Specialization

Improve your resume and LinkedIn with personalized feedback

Practice your skills with interactive tools and mock interviews

Plan your career move with Coursera’s job search guide

¹Lightcast™ Job Postings Report, United States, 1/1/22-12/31/22. ²Based on program graduate survey responses, United States 2021.

Gain the job-ready skills for an entry-level data analyst role through this Professional Certificate from IBM and position yourself competitively in the thriving job market for data analysts, which will see a 20% growth until 2028 (U.S. Bureau of Labor Statistics).

Power your data analyst career by learning the core principles of data analysis and gaining hands-on skills practice . You’ll work with a variety of data sources, project scenarios, and data analysis tools, including Excel, SQL, Python, Jupyter Notebooks, and Cognos Analytics, gaining practical experience with data manipulation and applying analytical techniques.

This Professional Certificate does not require any prior programming or statistical skills, and is suitable for learners with or without college degrees. All you need to get started is basic computer literacy, high school math, comfort working with numbers, willingness to learn, and a desire to enrich your profile with valuable skills.

Upon successful completion of this program, you’ll have analyzed real-world datasets, created interactive dashboards, and presented reports to share your findings, giving you the confidence and the portfolio to begin a career as an associate or junior data analyst. You’ll also build the foundation for other data disciplines such as data science or data engineering.

This program is ACE® recommended—when you complete, you can earn up to 12 college credits.

Applied Learning Project

Throughout the program, you’ll complete hands-on projects and labs and gain a firm grasp on the required technical skills to effectively gather, wrangle, mine, and visualize data, as well as the soft skills for working with stakeholders and storytelling with data to engage your audience. Projects

Import, clean, and analyze fleet vehicle inventory with Excel pivot tables.

Use car sales key performance indicator (KPI) data to create an interactive dashboard with visualizations.

Extract and graph financial data with the Pandas data analysis Python library.

Use SQL to query census, crime, and school demographic data sets.

Wrangle data, graph plots, and create regression models to predict housing prices with data science Python libraries.

Create a dynamic Python dashboard to monitor, report, and improve US domestic flight reliability.

At the end of the program, you complete a real-world capstone project specifically designed to showcase your newly learned data analyst skills.

Introduction to Data Analytics

Explain what Data Analytics is and the key steps in the Data Analytics process

Differentiate between different data roles such as Data Engineer, Data Analyst, Data Scientist, Business Analyst, and Business Intelligence Analyst

Describe the different types of data structures, file formats, and sources of data

Describe the data analysis process involving collecting, wrangling, mining, and visualizing data

Excel Basics for Data Analysis

Gain working knowledge of Excel for Data Analysis

Perform basic spreadsheet tasks including navigation, data entry, and using formulas.

Employ data quality techniques to import and clean data in Excel.

Analyze data in spreadsheets by using filtering, sorting, look-up functions, and pivot tables.

Data Visualization and Dashboards with Excel and Cognos

Create basic graphs such as line, bar, and pie charts using Excel spreadsheets.

Explain the important role charts play in telling a data-driven story.

Construct advanced charts and visualizations such as Treemaps, Sparklines, Histogram, Scatter Plots, and Filled Map Charts.

Build and share interactive dashboards using Excel and Cognos Analytics.

Python for Data Science, AI & Development

Describe Python Basics including Data Types, Expressions, Variables, and Data Structures.

Apply Python programming logic using Branching, Loops, Functions, Objects & Classes.

Demonstrate proficiency in using Python libraries such as Pandas, Numpy, and Beautiful Soup.

Access web data using APIs and web scraping from Python in Jupyter Notebooks.

Python Project for Data Science

Play the role of a Data Scientist / Data Analyst working on a real project.

Demonstrate your Skills in Python - the language of choice for Data Science and Data Analysis.

Apply Python fundamentals, Python data structures, and working with data in Python.

Build a dashboard using Python and libraries like Pandas, Beautiful Soup and Plotly using Jupyter notebook.

Databases and SQL for Data Science with Python

Analyze data within a database using SQL and Python.

Create a relational database on Cloud and work with tables.

Write SQL statements including SELECT, INSERT, UPDATE, and DELETE.

Build more powerful queries with advanced SQL techniques like views, transactions, stored procedures and joins.

Data Analysis with Python

Develop Python code for cleaning and preparing data for analysis - including handling missing values, formatting, normalizing, and binning data

Perform exploratory data analysis and apply analytical techniques to real-word datasets using libraries such as Pandas, Numpy and Scipy

Manipulate data using dataframes, summarize data, understand data distribution, perform correlation and create data pipelines

Build and evaluate regression models using machine learning scikit-learn library and use them for prediction and decision making

Data Visualization with Python

Implement data visualization techniques and plots using Python libraries, such as Matplotlib, Seaborn, and Folium to tell a stimulating story

Create different types of charts and plots such as line, area, histograms, bar, pie, box, scatter, and bubble

Create advanced visualizations such as waffle charts, word clouds, regression plots, maps with markers, & choropleth maps

Generate interactive dashboards containing scatter, line, bar, bubble, pie, and sunburst charts using the Dash framework and Plotly library

IBM Data Analyst Capstone Project

Apply different techniques to collect and wrangle data

Showcase your Data Analysis and Visualization skills

Create a data analysis report and a compelling presentation

Demonstrate proficiency with various Python Libraries

IBM is the global leader in business transformation through an open hybrid cloud platform and AI, serving clients in more than 170 countries around the world. Today 47 of the Fortune 50 Companies rely on the IBM Cloud to run their business, and IBM Watson enterprise AI is hard at work in more than 30,000 engagements. IBM is also one of the world’s most vital corporate research organizations, with 28 consecutive years of patent leadership. Above all, guided by principles for trust and transparency and support for a more inclusive society, IBM is committed to being a responsible technology innovator and a force for good in the world. For more information about IBM visit: www.ibm.com

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV

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Get a head start on your degree

When you complete this Professional Certificate, you can earn college credit if you apply and are accepted into one of the following online degree programs.

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coursera ibm data analyst capstone project github 2

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Frequently asked questions

What is the refund policy.

If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy Opens in a new tab .

Can I just enroll in a single course?

Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate, or you can audit it to view the course materials for free. When you subscribe to a course that is part of a Certificate, you’re automatically subscribed to the full Certificate. Visit your learner dashboard to track your progress.

Is this course really 100% online? Do I need to attend any classes in person?

This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.

What is data analysis?

Data analysis involves gathering, cleaning, organizing, modelling, and visualizing data with the goal of extracting helpful insights that can inform decision-making.

What jobs can I get with data analytics skills?

Data analytics skills will prove valuable in any profession. As data analytics technology develops, organizations across fields are increasingly using data to inform decision-making. This program will provide you with all the skills needed for an entry-level Data Analyst role, and will provide a strong foundation for future career development in other paths such as data science or data engineering.

How long does it take to complete the Professional Certificate?

This is a self-paced Professional Certificate that you can complete on your own schedule. Working 10-12 hours a week, you could complete the entire program in just 3 months. If working part time with just 2-3 hours per week, it can take up to 9 months.

What background knowledge is necessary?

No specialized background or degree is needed. However, you are expected to have basic computer literacy, high-school level mathematics, and be comfortable working with numbers.

Do I need to take the courses in a specific order?

It is highly recommended to complete the courses in the order they are listed, as they build upon concepts in the previous courses.

What will I be able to do upon completing the Professional Certificate?

Upon completing this Professional Certificate, you will be armed with the skills and knowledge to start an entry level role in Data Analytics. You can also apply your newly-acquired analytical skills to enrich your current career in a variety of industries including banking, accounting, and IT and functions such as marketing, finance, and research.

Data analytics skills are also valuable as an entry point to other data-related professions such as Data Science, Data Engineering, and Business Analytics.

Can I get college credit for taking the IBM Data Analyst Professional Certificate?

Yes. The IBM Data Analyst Professional Certificate recently secured a credit recommendation from the American Council on Education's (ACE) Credit Recommendation, which is the industry standard for translating workplace learning to college credit. Learners can earn a recommendation of 12 college credits for completing the program. This aims to help open up additional pathways to learners who are interested in higher education and prepare them for entry-level jobs.

How do you share your proof of completion with the educational institutions for transferring credit?

To share proof of completion with schools, certificate graduates will receive an email prompting them to claim their Credlybadge, which contains the ACE®️credit recommendation. Once claimed, you will receive a competency-based transcript that signifies the credit recommendation, which can be shared directly with a school from the Credly platform. Please note that the decision to accept specific credit recommendations is up to each institution and is not guaranteed.

Where can I find more information on ACE credit recommendations?

Please see Coursera’s ACE Recommendations FAQ.

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GitHub
A tag already exists with the provided branch name. Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. Capstone project for IBM Data analyst professional certificate
CAPSTONE IBM CYBERSECURITY ANALYST CERTIFICATION
Looking for help from course takers in IBM Specialization track. Can someone help to review my capstone? The Coursera Community is moving! I stuck at capstone project on data breach. i'm also stuck at this please
GitHub
A tag already exists with the provided branch name. Capstone_Where to buy a house in Stockholm_final.ipynb. Week 1-Capstone Project .ipynb
Data Engineering Capstone Project
In this course you will apply a variety of data engineering skills and techniques you have learned as part of ... IBM Data Engineering Professional Certificate IBM Skills Network. Showcase working knowledge with relational databases
Entrepreneurship Capstone
Lots of things to learn, Thank you Coursera and Enterepreneueship Capstone Team. Offered by University of Maryland, College Park
IBM Data Analyst Professional Certificate
Gain the job-ready skills for an entry-level data analyst role through this eight-course Professional Certificate from IBM and position yourself competitively in the thriving job market for data analysts