Organizer: Cisco Networking Academy.
Quintillion bytes of data are created EVERY day! Explore how data is transforming the world and opening up exciting new jobs. Cisco Course on Data Science with Certificate Online.
About the Course
- Course Free
- Duration: 6 Hours
- Level: Beginner
- Lab: 5 Labs
- Delivery Type: Self-paced
- Achievements: Badges & Certificates you can earn in this course.
- There are 20 questions in total.
- You must achieve 70% to pass this exam. You have unlimited attempts to pass the exam.
- Feedback is provided to direct you to areas that may require additional attention.
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This introductory course takes you inside the world of data science. You will learn the basics of data science, data analytics, and data engineering to understand how machine learning is shaping the future of business, healthcare, education, and more. Data science professionals who can provide actionable insights for data-driven decisions are in high demand all over the world.
Here’s what you will learn.
Module 1: Experience Analytics
Module 2: Data Collection and Storage
Module 3: Artificial Intelligence and Machine Learning
Module 4: Embarking on Your Career in Data Analytics
Introduction to Data Science
100% Correct Answers Cisco Course on Data Science Available Here
Question 1. An online e-commerce shopping site offers money-saving promotions for different products every hour. A data analyst would like to review the sales of products two days prior in the afternoon. Which data type would they search for in their query of the sales data?
Integer
String
Date and time
Floating point
Question 2. A sales manager in a large automobile dealership wants to determine the top four best selling models based on sales data over the past two years. Which two charts are suitable for the purpose? (Choose two.)
Bar chart
Pie chart
Line chart
Scatter chart
Column chart
Question 3. Refer to the exhibit. Match the column with the data type that it contains.
Shipped- Boolean
Revenue- Floating point
Quantity– Integer Order number– String
Product – String
Question 4. Which characteristic describes Boolean data?
A data type that identifies either a zero (0) or a one (1).
A text data type to store confidential information such as social security numbers.
A special text data type to be used for Fill-in-blank questions.
A data type that identifies either a true (T) state or a false (F) state.*
Question 5. What are three types of structured data? (Choose three.)
Blogs
White papers
Spreadsheet data*
E-commerce user accounts*
Newspaper articles
Data in relational databases*
Question 6. What is the most cost-effective way for businesses to store their big data?
Cloud storage*
On-premises
Onsite local servers
Onsite storage arrays
Question 7. What is a major challenge for storage of big data with on-premises legacy data warehouse architectures?
They cannot process the volume of big data.*
They cannot process unstructured data.
They cannot process structured data.
Additional servers cannot be easily added to the network architecture.
Question 8 What is unstructured data?
Data that does not fit into the rows and columns of traditional relational data storage systems.*
A large csv file.
Geolocation data.
Data that fits into the rows and columns of traditional relational data storage systems.
Question 9. Match the respective big data term to its description.
Velocity- Describes the rate at which data is generated.
Veracity– Is the process of preventing inaccurate data from spoiling data sets.
Variety- Describes a type of data that is not ready for processing and analysis.
Volume– Describes the amount of data being transported and stored.
Question 10. Changing the format, structure, or value of data takes place in which phase of the data pipeline?
Analysis
Storage
Transformation*
Ingestion
Question 11. Which type of machine learning algorithm would be used to train a system to detect spam in email messages?
Association
Classification*
Regression
Clustering
Question 12. Which step in a typical machine learning process involves testing the solution on the test data?
Data preparation
Learning process loop
Model evaluation*
Learning data
Question 13. What are two types of supervised machine learning algorithms? (Choose two.)
Regression*
Association
Mean
Clustering
Mode
Classification*
Question 14. Which type of learning algorithm can predict the value of a variable of a loan interest rate based on the value of other variables?
Classification
Association
Regression*
Clustering
Question 15. What are two applications that would gain ratification intelligence by using the reinforcement learning model? (Choose two.)
Robotics and industrial automation.*
Predicting the trajectory of a tornado using weather data.
Filtering email into spam or non-spam.
Identifying faces in a picture.
Playing video games.*
Question 16. Match the data professional role with the skill sets required.
Data scientist- Ability to use statistical and analytical skills, programming knowledge (Python, R, Java), and familiarity with Hadoop; a collection of open-source software utilities that facilitates working with massive amounts of data.
Data analyst- Ability to understand basic statistical principles, cleaning different types of data, data visualization, and exploratory data analysis.
Data engineer- Ability to understand basic statistical principles, cleaning different types of data, data visualization, and exploratory data analysis.
Question 17. Which skill set is important for someone seeking to become a data scientist?
The ability to ensure that the database remains stable and maintaining backups of the database and execute database updates and modifications.
A thorough knowledge of machine learning technologies and programming languages, strong statistical and analytical skills, and familiarity with software utilities that facilitates working with massive amounts of data.*
An understanding of basic statistical principles, cleaning different types of data, data visualization, and exploratory data analysis.
An understanding of architecture and distribution of data acquisition and storage, multiple programming languages (including Python and Java), and knowledge of SQL database design.
Question 18. Match the job title with the matching job description.
Data Engineer- Build and operationalize data pipelines for collecting and organizing data while ensuring the accessibility and availability of quality data.
Data Scientist– Apply statistics, machine learning, and analytic approaches in order to interpret and deliver visualized results to critical business questions.
Data Analyst- Leverage existing tools and problem-solving methods to query and process data, provide reports, summarize and visualize data.
Question 19. What are two job roles normally attributed to a data analyst? (Choose two.)
Turning raw data into information and insight, which can be used to make business decisions.*
Reviewing company databases and external sources to make inferences about data figures and complete statistical calculations.*
Using programming skills to develop, customize and manage integration tools, databases, warehouses, and analytical systems.
Building systems that collect, manage, and convert raw data into usable information.
Working in teams to mine big data for information that can be used to predict customer behavior and identify new revenue opportunities.
Question 20. A data analyst is building a portfolio for future prospective employers and wishes to include a previously completed project. What three process documentations would be included in building that portfolio? (Choose three.)
The failures of the unstructured data set selected.
The methods used to analyze the data.*
The hours spent on study and hours worked on projects.
The basis of choosing the respective data set.*
A list of data analytic tools that did not work in the described manner for the project.
The data-based research questions and research problem addressed in the respective project.*