This course is part of the Data Science with Databricks for Data Analysts Specialization

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stars
39 ratings

Emma Freeman +1 more instructor

5,732 already enrolled

Offered By

Data Science with Databricks for Data Analysts SpecializationDatabricks

About this Course

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In this course we're going to guide you through the fundamental building blocks of data science, one of the fastest-growing fields in the world! 
With the help of our industry-leading data scientists, we’ve designed this course to build ready-to-apply data science skills in just 15 hours of learning. First, we’ll give you a quick introduction to data science - what it is and how it is used to solve real-world problems. For the rest of the course, we'll teach you the skills you need to apply foundational data science concepts and techniques to solve these real-world problems. 

By the end of this course, you'll be able to leverage your existing data analysis skills to design, execute, assess, and communicate the results of your very own data science projects.

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.

Course 2 of 3 in the

Data Science with Databricks for Data Analysts Specialization

Intermediate Level

Intermediate-level experience with SQL

Approx. 18 hours to complete

English

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What you will learn

Apply foundational data science concepts and techniques to solve these real-world problems.
Design, execute, assess, and communicate the results of your very own data science projects.

Skills you will gain

Data Science
Data Analysis
Machine Learning

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.

Course 2 of 3 in the

Data Science with Databricks for Data Analysts Specialization

Intermediate Level

Intermediate-level experience with SQL

Approx. 18 hours to complete

English

Could your company benefit from training employees on in-demand skills?

Try Coursera for Business

Instructors

Instructor rating

4.64/5 (17 Ratings)

Emma Freeman

Technical Curriculum Developer

Databricks

7,117 Learners

2 Courses

Mark Roepke

Technical Curriculum Developer

Databricks

7,117 Learners

2 Courses

Offered by

Databricks

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Syllabus - What you will learn from this course

Week1

Week 1

1 hour to complete

Welcome to the Course

1 hour to complete

6 videos (Total 27 min), 2 readings, 1 quiz

Week2

Week 2

3 hours to complete

An Introduction to Data Science

3 hours to complete

8 videos (Total 31 min)

Week3

Week 3

3 hours to complete

Introductory Statistics for Data Science

3 hours to complete

19 videos (Total 53 min), 5 readings, 4 quizzes

19 videos

Module and Lesson Intro45sAn Introduction to Statistics4mDescriptive Statistics5mDescriptive Statistics Lab Intro18sInferential Statistics3mAn Introduction to Probability3mDiscrete Probability Lab Intro15sStatistics and Probability Review1mAn Introduction to Probability Distributions4mDiscrete Probability Distributions4mDiscrete Probability Distributions Applications2mProbability Distribution Lab Intro15sContinuous Probability Distributions5mProbability Distribution Review1mAn Introduction to Hypothesis Testing4mHypothesis Test Example2mTypes of Hypothesis Tests3mHypothesis Testing Lab Intro18sOutlier Detection with Probability Distributions3m

5 readings

Descriptive Statistics Lab10mBasic Rules of Discrete Probability10mDiscrete Probability Lab10mDiscrete Probability Lab10mHypothesis Testing Lab10m

4 practice exercises

Statistics30mProbability Distributions10mHypothesis Testing10mIntroductory Statistics for Data Science30m

Week4

Week 4

3 hours to complete

Connecting Data Science to the Real World

3 hours to complete

9 videos (Total 32 min)

9 videos

Module and Lesson Intro1mWhy Good Questions Matter4mChallenges with Solving Real-World Problems with Hypothesis Testing3mIntroduction to Machine Learning, Part 12mIntroduction to Machine Learning, Part 25mSupervised and Unsupervised Learning5mRegression and Classification4mClustering3mFraming Real-World Questions Activity1m

2 practice exercises

Basics of Machine Learning30mClassification, Regression and Clustering30m

Week5

Week 5

6 hours to complete

Practical Machine Learning

6 hours to complete

28 videos (Total 85 min), 7 readings, 7 quizzes

28 videos

Module and Lesson Introduction39sA Review of Supervised Learning and Regression1mLinear Regression Assumptions4mApplying Linear Regression2mAccuracy and Interpretability5mRegression Evaluation6mRegression Interpretation3mA Review of Regression Evaluation2mAn Introduction to In-sample and Out-of-sample Data2mEvaluating on the Test Set2mOverfitting and Underfitting3mOverfitting and Underfitting Lab Intro23sThe Bias-Variance Tradeoff1m The Bias-Variance Tradeoff and Model Generalization3mA Review of Key Concepts2mAn Introduction to Logistic Regression3mApplying Logistic Regression2mLogistic Regression Lab 1 Intro15sAssigning Classes Based on Probabilities3mClassification Evaluation7mLogistic Regression Lab 2 Intro16sAn Introduction to Decision Trees2mThe Decision Tree Training Algorithm7mDecision Tree Hyperparameters3mApplying Decision Trees2mDecision Tree Lab Intro19sDecision Trees for Regression2mExtending Decision Trees3m

7 readings

An Introduction to Linear Regression10mLinear Regression Lab 110mLinear Regression Lab 210m Overfitting and Underfitting Lab Activity10mLogistic Regression Lab I10mLogistic Regression Lab 210mDecision Tree Lab10m

7 practice exercises

Linear Regression30mRegression Evaluation30mBias-Variance Tradeoff 30mLogistic Regression30mClassification Evaluation30mDecision Trees 130mDecision Trees 230m

Week6

Week 6

3 hours to complete

Completing Data Science Projects

3 hours to complete

13 videos (Total 27 min), 2 readings, 3 quizzes

13 videos

Module Introduction1mLesson Introduction51sA Review of Problem Framing3mMeasurable Problem Objectives3mProblem Constraints5mBaseline Solutions3mBaseline Solutions Lab Intro45sMeasuring Solutions in the Real-World3mMachine Learning Solutions Discussion Intro1mLesson Introduction43sA Review of the Data Science Process2mData Science Project Lab Intro51sData Science Project Summary Activity36s

2 readings

Baseline Solutions Lab10mData Science Project Lab10m

2 practice exercises

Measuring Success and Constraints30mMachine Learning Solutions30m

Reviews

4.2

13 reviews

5 stars
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TOP REVIEWS FROM DATA SCIENCE FUNDAMENTALS FOR DATA ANALYSTS

by JMAug 4, 2022

The Databricks Data Science Fundamentals for Data Analysis coursera was outstanding. I found the lessons to be industry relavent, challenging, and fair.

by JSOct 24, 2022

Excellent, lucid and enriching, this is one of the best courses I have taken on Coursera. Kudos to the instructors.

View all reviews

About the Data Science with Databricks for Data Analysts Specialization

This specialization is intended for data analysts looking to expand their toolbox for working with data. Traditionally, data analysts have used tools like relational databases, CSV files, and SQL programming, among others, to perform their daily workflows. In this specialization, you will leverage existing skills to learn new ones that will allow you to utilize advanced technologies not traditionally linked to this role - technologies like Databricks and Apache Spark. By the end of this specialization, you'll be able to solve real-world business problems with Databricks and the most popular machine learning techniques.

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 Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, 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.
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.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

More questions? Visit the Learner Help Center.

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Data Science Fundamentals for Data Analysts

About this Course

What you will learn

Skills you will gain