Tools for Data Science Coursera Quiz Answers – 100% Correct Answers

Tools for Data Science Coursera Quiz Answers

Practice Quiz – Languages

Q1. Which of the following statements is true?

  • Keras, Scikit-Learn, Matplotlib, Pandas, and TensorFlow are all built with Python.
  • 80% of data scientists worldwide use Python.
  • Python is the most popular language in data science.
  • Python is useful for AI, machine learning, web development, and IoT.
  • All of the above

Q2. Which of the following are SQL databases? (Select all that apply.)

  • MongoDB
  • MariaDB
  • MySQL
  • PostgreSQL
  • CouchDB
  • Oracle

Q3. Which statements are true about Open Source and Free Software? (Select all that apply.)

  • Free Software and Open Source can be used interchangeably.
  • Free Software can always be run, studied, modified and redistributed with or without changes.
  • Most of Free Software licenses also qualify for Open Source.
  • Open Source Software can be modified without sharing the modified source code depending on the Open Source license.

Q4. Is the following statement true or false: “R integrates well with other computer languages like C++, Java, C, .Net and Python.”

  • True
  • False

Q5. Which of the following languages can be used for data science?

  • Julia
  • Java
  • Javascript
  • SQL
  • R
  • Scala
  • All of the above

Q6. Which of the following is used to make Artificial intelligence and Machine Learning possible? (Select all that apply.)

  • Oracle
  • PyTorch
  • TensorFlow.js
  • Apache Spark
  • GNU
  • Caffe

Practice Quiz – Tools

Q1. Which of the following are common tasks in data science?

  • Data Management
  • Model Monitoring and Assessment
  • Data Integration and Transformation
  • Model Building
  • Data Visualization
  • Model Deployment
  • All of the above

Q2. Which of the following are data management tools? (Select all that apply.)

  • GitHub
  • MySQL
  • PostgreSQL
  • KubeFlow
  • PixieDust

Q3. Which of the following are Data Integration and Transformation tools? (Select all that apply.)

  • Cassandra
  • Apache Kafka
  • Apache Nifi
  • Apache AirFlow
  • Ceph

Q4. Which statement about JupyterLab is correct?

  • JuypterLab can run Python code only.
  • JuypterLab can run R code only.
  • JuypterLab can run R and Python code only.
  • JuypterLab can run R and Python code in addition to other programming languages.

Q5. Which statement about RStudio is correct?

  • RStudio is the primary choice for development in the R programming language.
  • RStudio is the primary choice for web development.
  • RStudio is the primary choice for development in the Python programming language.

Q6. Which statements about IBM Watson Studio and OpenScale are correct? (Select all that apply.)

  • Watson Studio together with Watson OpenScale is a database management system.
  • Watson Studio together with Watson OpenScale covers the complete development life cycle for all data science, machine learning and AI tasks.
  • Watson Studio together with Watson OpenScale is available as a Cloud offering as well as a package running on top of Kubernetes/RedHat OpenShift in a local data center called IBM Cloud Pak for Data.

Practice Quiz – Packages, APIs, Data Sets, Models

Q1. Which scientific computing library provides data structures and data analysis tools for Python?

  • YumPies
  • Seahorse
  • Pandas
  • TensorFlow

Q2. What does the acronym API stand for?

  • Application Programming Interface
  • Arithmetic Programming Interface
  • Abstract Programming Interface
  • Abstract Python Interface

Q3. True or False: Open data is always distributed under a Community Data License Agreement.

  • True
  • False

Q4. Which of the following is not a type of Machine Learning?

  • Supervised learning
  • Supervised teaching
  • Reinforcement learning
  • Unsupervised learning

Q5. Which of the following is NOT a deep learning framework?

  • TensorFlow
  • PyTorch
  • Tommy
  • Keras

Q6. Fill in the blank: The MAX model-serving microservices expose a _________________ that applications use to consume a model.

  • Scala API
  • Java API
  • Python API

Graded Quiz

Q1. Which are the three most used languages for data science?

  • R, Python, SQL

Q2. Which of these is a database query language?

  • SQL

Q3. Is it possible to use machine learning within a web browser with Javascript?

  • Yes

Q4. Which of these is not a machine learning or deep learning library for Python?

  • NumPy

Q5. Comma Separated Values (CSV) is a commonly used format to store:

  • Tabular data

Q6. Classification models can be used to determine whether:

  • All of the Above

Q7. Generally speaking, which type of model is used to predict a numerical value, such as the potential sales price of a used car?

  • Regression model

Q8. Fill in the blank: ________________ is the heart of every organization.

  • Data

Q9. What does the “BI” in BI Tools stand for?

  • Business intelligence

Practice Quiz – Jupyter Notebook

Q1. Which of the following functions do Jupyter Notebooks unify?

  • All of the above

Q2. Which statement is true about Jupyter Notebooks?

  • Jupyter Notebooks are free and open source.

Q3. What is a Jupyter Notebook kernel?

  • It is a wrapper running on the Jupyter server encapsulating the programming language interpreter.

Practice Quiz – RStudio IDE

Q1. Which of the following functions does RStudio unify? (Select all that apply.)

  • b. Editing and execution of source code.
  • c. Display of the R Console.
  • d. Visualization of plots.
  • e. Visualization of data in table form.

Q2. Which statement is true about the R Studio IDE?

  • RStudio is free and open source.

Q3. Which statement about R packages is correct?

  • R currently supports more than 15,000 packages which can be installed to extend R’s functionality.

Practice Quiz – GitHub

Q1. Which of the following statements are true?

  • Git is a system for version control of source code
  • Git is very useful for data science as well since data science often involves a lot of source code to be written and managed.

Q2. Which of the following statements about repositories are correct? (Select all that apply.)

  • The local repository is only accessible by myself.
  • The staging is only accessible by myself.
  • The remote repository is accessible by all contributors.

Q3. What is the best process for contributing a bugfix to a foreign repository?

  • Fork the repository, update the fork and create a pull request.

Graded Quiz

Q1. Which are the two most used open-source tools for data science?

  • RStudio
  • Jupyter Notebooks/Jupyter Lab

Q2. What tool do most R developers use?

  • RStudio

Q3. What tool do most Python developers use?

  • Jupyter Notebooks or JupyterLab

Q4. True or false? Jupyter Notebooks / JupyterLab support development in R.

  • True

Q5. Which tool unifies documentation, source code, and data visualizations into a single document?

  • Jupyter Notebooks / JupyterLab

Q6. Which command is used to install packages in R?

  • install.packages(“package name”)

Q7. Which of the following functions does RStudio provide?

  • Editing and execution of R code.

Q8. True or False: The Jupyter Notebook kernel must be installed on a local server.

  • False

Q9. Which of the following statements about Jupyter Notebooks is correct?

  • Jupyter Notebooks support the Visualization of data in charts.

Q10. True or false? R studio supports development in Python.

  • True

Practice Quiz – Watson Studio

Q1. Fill in the blank: In Watson Studio, a ____________ is how you organize your resources to achieve a particular goal. Resources can include data, collaborators, and analytic assets like notebooks and models.

  • project

Q2. Fill in the blank: It’s a best practice to remove or replace _____________ before publishing to GitHub.

  • credentials

Q3. Which of the following do you need to create in order to publish a notebook to your GitHub repository?

  • Access token

Q4. Fill in the blank: If you’d like to schedule a notebook in Watson Studio to run at a different time you can create a(n) _____________.

  • job

Q5. Fill in the blank: On the environments tab you can define the _________________.
a. Runtime configuration for flow editor.

  • All of the above

Q6. Fill in the blank: When sharing a read only version of a notebook, you can choose to share __________________.

  • All of the above

Q7. Fill in the blank: When working in a Jupyter Notebook, before returning to a project, it’s important to ________________________.

  • Save your notebook

Q8. Fill in the blank: Before running a notebook, it’s a best practice to ____________ to describe what the notebook does.

  • Insert a cell at the top of the notebook

Q9. Fill in the blank: In the _____________ tab you can define the hardware size and software configuration for the runtime associated with Watson Studio tools such as notebooks.

  • environments

Q10. Fill in the blank: IBM Cloud uses ______________ as a way for you to organize your account resources in customizable groupings so that you can quickly assign users access to more than one resource at a time.

  • Resource groups

Practice Quiz – Other IBM Tools

Q1. Which products (of those we covered) allow you to build data pipelines using a graphical user interface and no coding?

  • IBM SPSS Modeler and Modeler Flows in Watson Studio

Q2. Which features of Data Refinery help save hours and days of data preparation?

  • All of the above

Q3. Watson Knowledge Catalog provides what functionality?

  • Catalog data and ML assets, help to find relevant assets, keep track of asset lineage, enforce data governance

Q4. Fill in the blank: PMML, PFA, and ONNX are __________________.

  • Opens standards for predictive model serialization, exchange, and deployment

Q5. Which node must be used in Modeler flows before any modeling node?

  • Type node

Q6. Fill in the blank: Auto Classification node can be used for data with ______________.

  • A categorical target variable

Q7. Fill in the blank: Auto Numeric node can be used for data with __________________.

  • A continuous target variable

Q8. IBM SPSS Modeler evolved from which product?

  • Clementine

Q9. Fill in the blank: IBM SPSS Statistics syntax can be created using ___________.

  • Graphical user interface the IBM SPSS statistics product or syntax editor

Q10. AutoAI provides which of the following services?

  • Automatic finding of optimal data preparation steps model selection and hyperparameter optimization

Q11. OpenScale provides which of the following services?

  • Monitoring for fairness, bias, and model drift

Q12. Predictive Model Markup Language (PMML) was created by which entity?

  • The Data Mining Group

Graded Quiz

Q1. Which feature in Watson Studio helps to keep track of and discover relevant Machine Learning assets?

  • Watson Knowledge Catalog

Q2. Data Refinery provides which of the following services?

  • Visualize and prepare data.

Q3. How does Data Refinery help build repeatable Data Pipelines for workloads of almost any size?

  • Create a scheduled job and use a custom environment to run the data flow/pipeline on different workloads

Q4. Modeler flows in Watson Studio always begin with which type of node?

  • A data source node

Q5. IBM SPSS Modeler includes what kind of models?

  • All of the above

Q6. What feature of IBM SPSS Statistics allows easy saving and modifying of previous tasks?

  • SPSS syntax

Q7. Open Neural Network eXchange (ONNX) was originally created for what models?

  • Deep learning models

Final Exam

My Jupyter Notebook on IBM Watson Studio

Thomas George Thomas

Data Scientist

I am interested in Data Science because I would love to contribute towards affordable and quality healthcare in the future

The below should print ‘Hello World’

print("Hello World!")

Hello World!

All Quiz Answers of multiple Specializations or Professional Certificate programs:

Course 1: What is Data Science?

Course 2: Tools for Data Science

Course 3: Data Science Methodology

Course 4: Python for Data Science, AI & Development

Course 5: Python Project for Data Science

Course 6: Databases and SQL for Data Science with Python

Course 7: Data Analysis with Python

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