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Yan Luo
and
Joseph Santarcangelo
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.
Read more
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.
Read more
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.
In this course you will assume the role of a Data Scientist working for a startup intending to compete with SpaceX, and in the process follow the Data Science methodology involving data collection, data wrangling, exploratory data analysis, data visualization, model development, model evaluation, and reporting your results to stakeholders.
You will be tasked with predicting if the first stage of the SpaceX Falcon 9 rocket will land successfully. With the help of your Data Science findings and models, the competing startup you have been hired by can make more informed bids against SpaceX for a rocket launch.
In this course, there will not be much new learning, instead you’ll focus on hands-on work to demonstrate and apply what you have learnt in previous courses. By successfully completing this Capstone you will have added a project to your data science and machine learning portfolio to showcase to employers.
Register for this course and see more details by visiting:
OpenCourser.com/course/vd8bcc/applied
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What's inside
Syllabus
Introduction
In this capstone, we will predict if the Falcon 9 first stage will land successfully. SpaceX advertises Falcon 9 rocket launches on its website, with a cost of 62 million dollars; other providers cost upward of 165 million dollars each, much of the savings is because SpaceX can reuse the first stage. Therefore if we can determine if the first stage will land, we can determine the cost of a launch. This information can be used if an alternate company wants to bid against SpaceX for a rocket launch. In this module, you will be provided with an overview of the problem and the tools you need to complete the course.
Read more
Syllabus
Introduction
In this capstone, we will predict if the Falcon 9 first stage will land successfully. SpaceX advertises Falcon 9 rocket launches on its website, with a cost of 62 million dollars; other providers cost upward of 165 million dollars each, much of the savings is because SpaceX can reuse the first stage. Therefore if we can determine if the first stage will land, we can determine the cost of a launch. This information can be used if an alternate company wants to bid against SpaceX for a rocket launch. In this module, you will be provided with an overview of the problem and the tools you need to complete the course.
Read more
Exploratory Data Analysis (EDA)
In this module, you will collect data on the Falcon 9 first-stage landings. You will use a RESTful API and web scraping. You will also convert the data into a dataframe and then perform some data wrangling.
Interactive Visual Analytics and Dashboard
In this module, you will build a dashboard to analyze launch records interactively with Plotly Dash. You will then build an interactive map to analyze the launch site proximity with Folium.
Predictive Analysis (Classification)
In this module, you will use machine learning to determine if the first stage of Falcon 9 will land successfully. You will split your data into training data and test data to find the best Hyperparameter for SVM, Classification Trees, and Logistic Regression. Then find the method that performs best using test data.
Present Your Data-Driven Insights
In this module, you will compile all of your activities into one place and deliver your data-driven insights to determine if the first stage of Falcon 9 will land successfully.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Develops skills, knowledge, and tools used in industry and practice
Builds a strong foundation for beginners in data science
Offers hands-on labs and interactive materials
Requires extensive background knowledge
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Reviews summary
Data expertise
learners say this course is largely positive for beginners and those who want to refresh data science skills.
According to students, the course can be challenging, especially for those new to programming or data science. However, many say the course is well-structured and provides opportunities to practice skills with real-world data sets.
Learners also say the course provides a comprehensive review of data science concepts and tools, and that the hands-on projects are helpful for applying those concepts to real-world problems.
Students also appreciate that the course is self-paced and can be completed at your own pace.
Overall, learners say this course is a valuable resource for anyone interested in learning more about data science, and that it can help you prepare for a career in the field.
self-paced and can be completed at your own pace
largely positive for...those who want to refresh data science skills
"provides a comprehensive review of data science concepts and tools"
largely positive for beginners
"well-structured and provides opportunities to practice skills with real-world data sets."
engaging assignments with real-world data sets
"The hands-on projects are helpful for applying those concepts to real-world problems"
Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Applied Data Science Capstone with these
activities:
Review Python Web Scraping Fundamentals
Show steps
Grasping the fundamentals of web scraping will set a solid foundation for data collection tasks in this course.
Show steps
-
Follow a guided tutorial on web scraping with Python.
-
Practice web scraping on a simple website.
Review Linear Algebra Concepts
Show steps
Revisiting linear algebra concepts will strengthen the mathematical foundation for data science techniques.
Browse courses on
Linear Algebra
Show steps
-
Review key linear algebra concepts (e.g., vectors, matrices, transformations).
-
Solve practice problems to reinforce understanding.
Discuss Data Science Techniques with Peers
Show steps
Engaging in peer discussions fosters knowledge sharing, diverse perspectives, and reinforces learning.
Show steps
-
Join a study group or online forum.
-
Participate in discussions and ask questions.
-
Share your own insights and help others.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Attend a Machine Learning Workshop
Show steps
Participating in workshops provides opportunities for hands-on learning and networking with experts.
Show steps
-
Research and identify relevant machine learning workshops.
-
Register and attend the workshop.
-
Actively participate and ask questions.
Build a Dashboard to Visualize SpaceX Launch Data
Show steps
Building an interactive dashboard will provide hands-on experience with data visualization and analysis techniques covered in the course.
Browse courses on
Dashboard Creation
Show steps
-
Choose a data visualization library (e.g., Plotly, Dash).
-
Create a dashboard to visualize key SpaceX launch data.
-
Deploy the dashboard online for easy access.
Practice Model Selection for Classification
Show steps
Regular practice with model selection and evaluation will enhance understanding and proficiency in this crucial aspect of data science.
Browse courses on
Model Selection
Show steps
-
Review different classification algorithms.
-
Practice selecting and tuning models using cross-validation.
Present Data-Driven Insights to Stakeholders
Show steps
Creating a presentation for stakeholders simulates real-world scenarios and tests students' ability to communicate data-driven insights effectively.
Browse courses on
Data Presentation
Show steps
-
Prepare a presentation outlining your findings and recommendations.
-
Practice delivering the presentation.
-
Present to a group of peers or mentors.
Review Python Web Scraping Fundamentals
Show steps
Grasping the fundamentals of web scraping will set a solid foundation for data collection tasks in this course.
Show steps
Show steps
Show steps
- Follow a guided tutorial on web scraping with Python.
- Practice web scraping on a simple website.
Review Linear Algebra Concepts
Show steps
Revisiting linear algebra concepts will strengthen the mathematical foundation for data science techniques.
Browse courses on
Linear Algebra
Show steps
Show steps
Show steps
- Review key linear algebra concepts (e.g., vectors, matrices, transformations).
- Solve practice problems to reinforce understanding.
Discuss Data Science Techniques with Peers
Show steps
Engaging in peer discussions fosters knowledge sharing, diverse perspectives, and reinforces learning.
Show steps
Show steps
Show steps
- Join a study group or online forum.
- Participate in discussions and ask questions.
- Share your own insights and help others.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Attend a Machine Learning Workshop
Show steps
Participating in workshops provides opportunities for hands-on learning and networking with experts.
Show steps
Show steps
Show steps
- Research and identify relevant machine learning workshops.
- Register and attend the workshop.
- Actively participate and ask questions.
Build a Dashboard to Visualize SpaceX Launch Data
Show steps
Building an interactive dashboard will provide hands-on experience with data visualization and analysis techniques covered in the course.
Browse courses on
Dashboard Creation
Show steps
Show steps
Show steps
- Choose a data visualization library (e.g., Plotly, Dash).
- Create a dashboard to visualize key SpaceX launch data.
- Deploy the dashboard online for easy access.
Practice Model Selection for Classification
Show steps
Regular practice with model selection and evaluation will enhance understanding and proficiency in this crucial aspect of data science.
Browse courses on
Model Selection
Show steps
Show steps
Show steps
- Review different classification algorithms.
- Practice selecting and tuning models using cross-validation.
Present Data-Driven Insights to Stakeholders
Show steps
Creating a presentation for stakeholders simulates real-world scenarios and tests students' ability to communicate data-driven insights effectively.
Browse courses on
Data Presentation
Show steps
Show steps
Show steps
- Prepare a presentation outlining your findings and recommendations.
- Practice delivering the presentation.
- Present to a group of peers or mentors.
Career center
Learners who complete Applied Data Science Capstone will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
A Data Scientist is responsible for providing crucial insights from data to help organizations make informed decisions. You will use your knowledge of machine learning, statistics, and programming to analyze and interpret large datasets. This course will provide you with the necessary skills to become a successful Data Scientist, including data collection, wrangling, visualization, and model development. With the hands-on experience you gain in this course, you will be well-prepared to enter or advance your career in Data Science.
Machine Learning Engineer
Machine Learning Engineer
A Machine Learning Engineer designs, develops, and deploys machine learning models to solve complex problems. You will use your knowledge of machine learning algorithms, programming, and cloud computing to build and maintain models that can make predictions or decisions based on data. This course will provide you with the necessary skills to become a successful Machine Learning Engineer, including model development, evaluation, and deployment. With the hands-on experience you gain in this course, you will be well-prepared to enter or advance your career in Machine Learning Engineering.
Data Analyst
Data Analyst
A Data Analyst is responsible for collecting, cleaning, and analyzing data to help organizations understand their customers, products, and operations. You will use your knowledge of statistics, programming, and data visualization to extract insights from data and communicate them to stakeholders. This course will provide you with the necessary skills to become a successful Data Analyst, including data collection, wrangling, visualization, and statistical analysis. With the hands-on experience you gain in this course, you will be well-prepared to enter or advance your career in Data Analytics.
Business Intelligence Analyst
Business Intelligence Analyst
A Business Intelligence Analyst is responsible for using data to help organizations make better decisions. You will use your knowledge of data analysis, business intelligence tools, and data visualization to identify trends, patterns, and opportunities in data. This course will provide you with the necessary skills to become a successful Business Intelligence Analyst, including data collection, wrangling, visualization, and statistical analysis. With the hands-on experience you gain in this course, you will be well-prepared to enter or advance your career in Business Intelligence.
Data Engineer
Data Engineer
A Data Engineer is responsible for designing, building, and maintaining data pipelines and infrastructure. You will use your knowledge of data engineering tools, programming, and cloud computing to ensure that data is available, reliable, and secure. This course will provide you with the necessary skills to become a successful Data Engineer, including data collection, wrangling, storage, and processing. With the hands-on experience you gain in this course, you will be well-prepared to enter or advance your career in Data Engineering.
Data Visualization Specialist
Data Visualization Specialist
A Data Visualization Specialist is responsible for creating visual representations of data to help organizations understand their customers, products, and operations. You will use your knowledge of data visualization tools, design principles, and human perception to create visualizations that are clear, concise, and actionable. This course will provide you with the necessary skills to become a successful Data Visualization Specialist, including data visualization techniques, design principles, and user experience. With the hands-on experience you gain in this course, you will be well-prepared to enter or advance your career in Data Visualization.
Statistician
Statistician
A Statistician is responsible for collecting, analyzing, and interpreting data to help organizations make informed decisions. You will use your knowledge of statistics, probability, and data analysis to design studies, collect data, and draw conclusions from data. This course will provide you with the necessary skills to become a successful Statistician, including data collection, wrangling, visualization, and statistical analysis. With the hands-on experience you gain in this course, you will be well-prepared to enter or advance your career in Statistics.
Quantitative Analyst
Quantitative Analyst
A Quantitative Analyst is responsible for using mathematical and statistical models to analyze financial data to help organizations make investment decisions. You will use your knowledge of statistics, probability, and financial modeling to develop and implement models that can predict future financial performance. This course may provide you with some of the necessary skills to become a successful Quantitative Analyst, including data analysis, statistical modeling, and financial modeling. However, you may need to supplement your learning with additional courses or training in finance and financial modeling.
Operations Research Analyst
Operations Research Analyst
An Operations Research Analyst is responsible for using mathematical and analytical techniques to solve complex problems in business and industry. You will use your knowledge of optimization, simulation, and data analysis to develop and implement solutions that improve efficiency, productivity, and profitability. This course may provide you with some of the necessary skills to become a successful Operations Research Analyst, including data analysis, optimization, and simulation. However, you may need to supplement your learning with additional courses or training in operations research.
Data Architect
Data Architect
A Data Architect is responsible for designing and managing data architectures to ensure that data is available, reliable, and secure. You will use your knowledge of data modeling, database design, and data integration to design and implement data architectures that meet the needs of the organization. This course may provide you with some of the necessary skills to become a successful Data Architect, including data modeling, database design, and data integration. However, you may need to supplement your learning with additional courses or training in data architecture.
Software Engineer
Software Engineer
A Software Engineer is responsible for designing, developing, and maintaining software applications. You will use your knowledge of programming languages, software development tools, and software engineering principles to create software that meets the needs of users. This course may provide you with some of the necessary skills to become a successful Software Engineer, including programming, software development, and software engineering principles. However, you may need to supplement your learning with additional courses or training in software engineering.
Computer Scientist
Computer Scientist
A Computer Scientist is responsible for conducting research in computer science and developing new technologies. You will use your knowledge of computer science theory, algorithms, and data structures to develop new ways to solve problems and improve the performance of computers. This course may provide you with some of the necessary skills to become a successful Computer Scientist, including data structures, algorithms, and computer science theory. However, you may need to supplement your learning with additional courses or training in computer science.
Information Technology Specialist
Information Technology Specialist
An Information Technology Specialist is responsible for providing technical support and assistance to users of computer systems and networks. You will use your knowledge of computer hardware, software, and networks to troubleshoot problems, resolve issues, and provide training to users. This course may provide you with some of the necessary skills to become a successful Information Technology Specialist, including computer hardware, software, and networks. However, you may need to supplement your learning with additional courses or training in information technology.
Database Administrator
Database Administrator
A Database Administrator is responsible for managing and maintaining databases to ensure that data is available, reliable, and secure. You will use your knowledge of database management systems, data storage, and data security to design, implement, and maintain databases that meet the needs of the organization. This course may provide you with some of the necessary skills to become a successful Database Administrator, including database management systems, data storage, and data security. However, you may need to supplement your learning with additional courses or training in database administration.
Web Developer
Web Developer
A Web Developer is responsible for designing, developing, and maintaining websites. You will use your knowledge of web development languages, frameworks, and tools to create websites that are user-friendly, interactive, and accessible. This course may provide you with some of the necessary skills to become a successful Web Developer, including web development languages, frameworks, and tools. However, you may need to supplement your learning with additional courses or training in web development.
For more career information including salaries, visit:
OpenCourser.com/course/vd8bcc/applied
Reading list
We've selected 15 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Applied Data Science Capstone.
Save
Provides a comprehensive introduction to deep learning concepts and algorithms.
Provides a practical introduction to machine learning, with a focus on Python libraries such as Scikit-Learn, Keras, and TensorFlow. It would be a valuable resource for students who want to learn more about machine learning algorithms and techniques.
Provides a comprehensive introduction to machine learning for finance.
Provides a practical guide to building and deploying machine learning models using popular Python libraries.
Provides a comprehensive introduction to Bayesian data analysis.
Provides a comprehensive introduction to causal inference.
Provides a comprehensive overview of data science, including data collection, wrangling, analysis, and visualization. It would be a useful reference for students who want to learn more about the data science process.
Provides a comprehensive reference for using Python for data analysis.
Provides a practical guide to using SAS Enterprise Miner for predictive analytics.
Provides a comprehensive reference for statistical methods used in data analysis.
Provides a business-oriented perspective on data science.
Save
Provides a comprehensive overview of data mining techniques and algorithms.
Save
Provides a practical guide to creating effective data visualizations.
Save
Provides a practical guide to building and deploying predictive models.
Provides a gentle introduction to machine learning concepts and techniques.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/vd8bcc/applied
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Data Science: Capstone
Effort
5 weeks of study, approximately 45 hours in total (10-15 hours/week for the later modules)
Level
Intermediate
Via
Coursera
Institution
IBM
Instructors
Yan Luo
Joseph Santarcangelo
Language
English
Transcripts
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Good to know
Develops skills, knowledge, and tools used in industry and practice
Builds a strong foundation for beginners in data science
Offers hands-on labs and interactive materials
Requires extensive background knowledge
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