This course is part of the CertNexus Certified Data Science Practitioner Professional Certificate

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Sarah Haq +2 more instructors

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CertNexus Certified Data Science Practitioner Professional CertificateCertNexus

About this Course

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This course is designed for business professionals that want to learn how to analyze data to gain insight, use statistical analysis methods to explore the underlying distribution of data, use visualizations such as histograms, scatter plots, and maps to analyze data and preprocess data to produce a dataset ready for training.
The typical student in this course will have several years of experience with computing technology, including some aptitude in computer programming.

Flexible deadlines

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Shareable Certificate

Earn a Certificate upon completion

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Coursera Labs

Includes hands on learning projects.

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Course 3 of 5 in the

CertNexus Certified Data Science Practitioner Professional Certificate

Intermediate Level

Understand data science concepts, experience with programming languages (Python), libraries (NumPy,pandas) and database querying languages (SQL).

Approx. 20 hours to complete

English

Skills you will gain

Data Insight
Data Analysis
Dissemination
Preprocess Data
Data Visualization (DataViz)

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Coursera Labs

Includes hands on learning projects.

Learn more about Coursera Labs

Course 3 of 5 in the

CertNexus Certified Data Science Practitioner Professional Certificate

Intermediate Level

Understand data science concepts, experience with programming languages (Python), libraries (NumPy,pandas) and database querying languages (SQL).

Approx. 20 hours to complete

English

Instructors

Instructor rating

4.71/5 (7 Ratings)

Offered by

CertNexus

Syllabus - What you will learn from this course

Week1

Week 1

2 hours to complete

Examine Data

In the previous course in this specialization, you conducted extract, transform, and load (ETL) to ensure your data was ready for the next phase of the data science process: analysis. In some cases, an analysis of the data may be the actual final goal of the project, or it may be an important intermediary step on the road to machine learning. In either case, analyzing your data using various techniques will help you obtain useful insights into that data and what it represents. It'll also give you a better understanding of how the data needs to undergo more processing to prepare it for machine learning. You'll begin your analysis efforts by exploring the nature of your dataset and the relationships it contains.

2 hours to complete

10 videos (Total 47 min), 2 readings, 1 quiz

Week2

Week 2

2 hours to complete

Explore the Underlying Distribution of Data

2 hours to complete

9 videos (Total 54 min), 2 readings, 1 quiz

Week3

Week 3

5 hours to complete

Use Visualizations to Analyze Data

5 hours to complete

8 videos (Total 38 min), 7 readings, 2 quizzes

8 videos

Visualizations3mHistograms3mBox Plots and Violin Plots8mScatter Plots, Line Plots, and Area Plots6mBar Charts2mGeographical Maps and Heatmaps5mPlots in Combination (Bar Chart Grid)5mPlots in Combination (Pair Plot)2m

7 readings

Overview2mGuidelines for Analyzing Data Using Histograms3mGuidelines for Analyzing Data Using Box Plots and Violin Plots3mGuidelines for Analyzing Data Using Scatter Plots, Line Plots, and Area Plots5mGuidelines for Analyzing Data Using Bar Charts5mGuidelines for Analyzing Data Using Maps5mGuidelines for Using Visualizations to Analyze Data5m

1 practice exercise

Using Visualizations to Analyze Data 30m

Week4

Week 4

7 hours to complete

Preprocess Data

7 hours to complete

9 videos (Total 51 min), 11 readings, 2 quizzes

9 videos

Data Preprocessing6mMissing Values9mFeature Scaling6mFeature Engineering3mData Encoding5mContinuous Variable Discretization3mBin Determination3mFeature Splitting5mDimensionality Reduction6m

11 readings

Overview2mGuidelines for Handling Missing Values5mAdditional Transformation Functions10mGuidelines for Applying Transformation Functions to Datasets3mData Encoding Methods20mGuidelines for Encoding Data5mGuidelines for Discretizing Variables5mGuidelines for Splitting Features5mDimensionality Reduction Methods20m Guidelines for Performing Dimensionality Reduction3m Guidelines for Preprocessing Data5m

1 practice exercise

Preprocessing Data30m

About the CertNexus Certified Data Science Practitioner Professional Certificate

The field of Data Science has topped the Linked In Emerging Jobs list for the last 3 years with a projected growth of 28% annually and the World Economic Forum lists Data Analytics and Scientists as the top emerging job for 2022.

Data can reveal insights and inform business—by guiding decisions and influencing day-to-day operations. This specialization will teach learners how to analyze, understand, manipulate, and present data within an effective and repeatable process framework and will enable you to bring value to the business by putting data science concepts into practice. This course is designed for business professionals that want to learn how to more effectively extract insights from their work and leverage that insight in addressing business issues, thereby bringing greater value to the business. The typical student in this course will have several years of experience with computing technology, including some aptitude in computer programming. Certified Data Science Practitioner (CDSP) will prepare learners for the CertNexus CDSP certification exam. To complete your journey to the CDSP Certification Complete the Coursera Certified Data Science Practitioner Professional Certificate. Review the CDSP Exam Blueprint. Purchase your CDSP Exam Voucher. Register for your CDSP Exam.

CertNexus Certified Data Science Practitioner

Frequently Asked Questions

When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Certificate?
When you enroll in the course, you get access to all of the courses in the Certificate, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

More questions? Visit the Learner Help Center.

Analyze Data

About this Course

Skills you will gain

Instructors

Sarah Haq

Stacey McBrine

Megan Smith Branch

Offered by

CertNexus

Syllabus - What you will learn from this course

Examine Data

Explore the Underlying Distribution of Data

Use Visualizations to Analyze Data

Preprocess Data

Apply What You've Learned

About the CertNexus Certified Data Science Practitioner Professional Certificate

Frequently Asked Questions

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Analyze Data

About this Course

Skills you will gain

Instructors

Sarah Haq

Stacey McBrine

Megan Smith Branch

Offered by

CertNexus

Syllabus - What you will learn from this course

Examine Data

Explore the Underlying Distribution of Data

Use Visualizations to Analyze Data

Preprocess Data

Apply What You've Learned

About the CertNexus Certified Data Science Practitioner Professional Certificate

Frequently Asked Questions

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Learn Something New

Popular Data Science Courses

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