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⇱ Data Science & Machine Learning Fundamentals | Coursera


Data Science & Machine Learning Fundamentals

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Data Science & Machine Learning Fundamentals

2,631 already enrolled

Included with

Gain insight into a topic and learn the fundamentals.
4.8

16 reviews

Beginner level
No prior experience required
6 hours to complete

Gain insight into a topic and learn the fundamentals.
4.8

16 reviews

Beginner level
No prior experience required
6 hours to complete

Build your subject-matter expertise

This course is part of the Practical Data Science for Data Analysts Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate

There are 9 modules in this course

Data science is about using statistics to draw insights from data to drive action and improve business performance.

This course will guide you through the world of data science and machine learning, using applied examples to demonstrate real-world applications. Whether you’re an aspiring data scientist or a c-level exec, this course will bring you up to speed on everything data science. You’ll be introduced to machine learning, classification, exploratory data analysis, feature selection, and feature engineering—what they mean and how they are relevant to your business. We’ll start by defining the skills, tools, and roles behind data science that work together to create insights. We’ll then walk through regression and classification—the most common predictive and statistical techniques. Finally, you will understand why having a basic understanding of data science outputs is essential to all business stakeholders and how we can use those outputs to make business decisions. Whether you are a business leader or an aspiring analyst exploring data science, this Data Science & Machine Learning Fundamentals course will serve as your comprehensive introduction to this fascinating subject. You’ll learn all the key terminology to allow you to talk data science with your teams, begin implementing analysis, and understand how data science can help your business.

We’ll start by defining the skills, tools, and roles behind data science that work together to create insights. We’ll then walk through regression and classification—the most common predictive and statistical techniques. Finally, we will understand why having a basic understanding of data science outputs is essential to all business stakeholders and how we can use those outputs to make business decisions.

What's included

1 video1 reading

1 videoTotal 2 minutes
  • Course Introduction2 minutes
1 readingTotal 10 minutes
  • Downloadable Learner Files10 minutes

What's included

11 videos1 reading3 plugins

11 videosTotal 25 minutes
  • Data Science - Definitions and Examples4 minutes
  • Types of Analysis1 minute
  • Data Science Skills2 minutes
  • Two Types of Computer Science1 minute
  • The Data Science Process3 minutes
  • Machine Learning Terminology2 minutes
  • Types of Data Science Models3 minutes
  • More Types of Data Science Models2 minutes
  • Data Science Tools2 minutes
  • Data Science Roles3 minutes
  • What about Artificial Intelligence2 minutes
1 readingTotal 10 minutes
  • Area of Interest Poll10 minutes
3 pluginsTotal 41 minutes
  • Interactive Exercise 11 minute
  • Interactive Exercise 220 minutes
  • Interactive Exercise 320 minutes

What's included

10 videos1 plugin

10 videosTotal 21 minutes
  • Regression - Theory & Business Objectives2 minutes
  • Simple & Multiple Linear Regression3 minutes
  • Ordinary Least Squares2 minutes
  • Interpreting Coefficients2 minutes
  • Training and Testing1 minute
  • Underfitting and Overfitting1 minute
  • Plotting a Line of Best Fit in Excel3 minutes
  • Calculating the Optimal Line3 minutes
  • Regression in Python4 minutes
  • Other Regression Techniques2 minutes
1 pluginTotal 20 minutes
  • Interactive Exercise 420 minutes

What's included

13 videos1 plugin

13 videosTotal 30 minutes
  • Classification - Theory & Business Objectives3 minutes
  • Classification Models1 minute
  • Logistic Regression2 minutes
  • Decision Trees2 minutes
  • KNN - K Nearest Neighbors3 minutes
  • SVM - Support Vector Machines2 minutes
  • Naive Bayes3 minutes
  • Gaussian Naive Bayes1 minute
  • Confusion Matrix4 minutes
  • Evaluation Metrics2 minutes
  • Overfitting and Underfitting1 minute
  • Logistic Regression in Excel with RegressitLogistic3 minutes
  • Classification in Python4 minutes
1 pluginTotal 10 minutes
  • Interactive Exercise 510 minutes

What's included

4 videos

4 videosTotal 8 minutes
  • Leadership is Essential1 minute
  • Model Objectives3 minutes
  • Model Limitations2 minutes
  • Evaluation Metrics3 minutes

What's included

21 videos3 plugins

21 videosTotal 42 minutes
  • Data Preparation & Terminology2 minutes
  • Data Cleansing Part 13 minutes
  • Data Cleansing Part 22 minutes
  • Data Cleansing - Solutions3 minutes
  • EDA Part 1 - Data Types3 minutes
  • EDA - Data Type Exceptions1 minute
  • EDA - Descriptive Stats - Binary Variables2 minutes
  • EDA - Descriptive Stats - Unordered Categories2 minutes
  • EDA - Descriptive Stats - Ordered Categories2 minutes
  • Descriptive Stats - Continuous Variables1 minute
  • EDA - Correlation & the Correlation Matrix4 minutes
  • EDA - Scatterplot Matrix2 minutes
  • Feature Selection2 minutes
  • Feature Engineering - Outliers2 minutes
  • Feature Engineering - Scaling Methods2 minutes
  • Feature Engineering - Grouping and Binning2 minutes
  • Training & Testing2 minutes
  • Data Prep in Python - Import & Explore2 minutes
  • Data Prep in Python - Correlation Matrix1 minute
  • Data Prep in Python - One Hot Encoding1 minute
  • Data Prep in Python - Train/Test Split1 minute
3 pluginsTotal 35 minutes
  • Interactive Exercise 610 minutes
  • Interactive Exercise 715 minutes
  • Interactive Exercise 810 minutes

What's included

7 videos

7 videosTotal 12 minutes
  • Ensemble Models1 minute
  • Unsupervised Learning2 minutes
  • Reinforcement Learning2 minutes
  • Neural Networks & Deep Learning2 minutes
  • Rule Based Models1 minute
  • Monte Carlo Simulation2 minutes
  • Other Statistical Models2 minutes

What's included

2 videos

2 videosTotal 4 minutes
  • Course Summary3 minutes
  • Data Science Fundamentals Conclusion1 minute

What's included

1 assignment

1 assignmentTotal 75 minutes
  • Qualified Assessment75 minutes

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Instructor

Corporate Finance Institute
50 Courses150,669 learners

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Frequently asked questions

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