This course is part of the CertNexus Certified Artificial Intelligence Practitioner Professional Certificate

Renée Cummings

Offered By

CertNexus Certified Artificial Intelligence Practitioner Professional CertificateCertNexus

About this Course

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Machine learning is not just a single task or even a small group of tasks; it is an entire process, one that practitioners must follow from beginning to end. It is this process—also called a workflow—that enables the organization to get the most useful results out of their machine learning technologies. No matter what form the final product or service takes, leveraging the workflow is key to the success of the business's AI solution. 
This second course within the Certified Artificial Intelligence Practitioner (CAIP) professional certificate explores each step along the machine learning workflow, from problem formulation all the way to model presentation and deployment. The overall workflow was introduced in the previous course, but now you'll take a deeper dive into each of the important tasks that make up the workflow, including two of the most hands-on tasks: data analysis and model training. You'll also learn about how machine learning tasks can be automated, ensuring that the workflow can recur as needed, like most important business processes.

Ultimately, this course provides a practical framework upon which you'll build many more machine learning models in the remaining courses.

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 2 of 5 in the

CertNexus Certified Artificial Intelligence Practitioner Professional Certificate

Intermediate Level

General knowledge of AI is required, as is experience with Python or similar languages. Basic knowledge of math and statistics is also recommended.

Approx. 19 hours to complete

English

What you will learn

Collect and prepare a dataset to use for training and testing a machine learning model.
Analyze a dataset to gain insights.
Set up and train a machine learning model as needed to meet business requirements.
Communicate the findings of a machine learning project back to the organization.

Skills you will gain

Artificial Intelligence (AI)
Machine Learning
Data Analysis
Modeling
Process Management

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 2 of 5 in the

CertNexus Certified Artificial Intelligence Practitioner Professional Certificate

Intermediate Level

General knowledge of AI is required, as is experience with Python or similar languages. Basic knowledge of math and statistics is also recommended.

Approx. 19 hours to complete

English

Instructor

Renée Cummings

Founder and CEO, Urban AI, LLC

Certification Contributor

16,134 Learners

5 Courses

Offered by

CertNexus

Syllabus - What you will learn from this course

Week1

Week 1

2 hours to complete

Collect the Dataset

2 hours to complete

9 videos (Total 31 min), 3 readings, 2 quizzes

9 videos

Follow a Machine Learning Workflow Course Introduction2mCAIP Specialization Introduction3mCollect the Dataset Module Introduction1mMachine Learning Datasets2mData Structure Terminology4mData Quality Issues5mData Sources3mGuidelines for Selecting a Machine Learning Dataset4mETL and Machine Learning Pipelines4m

3 readings

Overview2mOpen Datasets15mGuidelines for Loading a Dataset5m

2 practice exercises

Open Datasets Quiz5mCollecting the Dataset30m

Week2

Week 2

4 hours to complete

Analyze the Dataset

4 hours to complete

15 videos (Total 38 min), 5 readings, 1 quiz

15 videos

Analyze the Dataset Module Introduction1mDataset Content and Format2mDistributions1mDescriptive Statistical Analysis1mCentral Tendency2mVariability and Range2mVariance and Standard Deviation7mSkewness1mKurtosis3mCorrelation Coefficient3mVisualizations2mHistogram41sBox Plot1mScatterplot2mMaps2m

5 readings

Overview2mGuidelines for Exploring the Structure of a Dataset5mStatistical Moments2mGuidelines for Analyzing a Dataset10mGuidelines for Using Visualizations to Analyze Data5m

1 practice exercise

Analyzing the Dataset30m

Week3

Week 3

2 hours to complete

Prepare the Dataset

2 hours to complete

9 videos (Total 24 min), 4 readings, 2 quizzes

9 videos

Prepare the Dataset Module Introduction1mData Preparation2mData Types2mContinuous vs. Discrete Variables1mData Encoding4mDimensionality Reduction3mMissing and Duplicate Values3mNormalization and Standardization2mHoldout Method2m

4 readings

Overview2mOperations You Can Perform on Different Types of Data10mSummarization2mGuidelines for Preparing Training and Testing Data3m

2 practice exercises

Data Types Quiz5mPreparing the Dataset30m

Week4

Week 4

4 hours to complete

Set Up and Train a Model

4 hours to complete

13 videos (Total 43 min), 3 readings, 1 quiz

13 videos

Set Up and Train a Model Module Introduction1mDesign of Experiments2mHypothesis Testing8mp-value and Confidence Interval3mMachine Learning Algorithms1mIterative Tuning1mBias and Generalizations5mCross-Validation4mFeature Transformation3mThe Bias–Variance Tradeoff2mParameters2mRegularization1mTraining Efficiency2m

3 readings

Overview2mGuidelines for Setting Up a Machine Learning Model2mGuidelines for Training and Tuning the Model3m

1 practice exercise

Setting Up and Training the Model30m

About the CertNexus Certified Artificial Intelligence Practitioner Professional Certificate

The Certified Artificial Intelligence Practitioner™ (CAIP) specialization prepares learners to earn an industry validated certification which will differentiate themselves from other job candidates and demnstrate proficiency in the concepts of Artificial intelligence (AI) and machine learning (ML) found in CAIP.

AI and ML have become an essential part of the toolset for many organizations. When used effectively, these tools provide actionable insights that drive critical decisions and enable organizations to create exciting, new, and innovative products and services. This specialization shows you how to apply various approaches and algorithms to solve business problems through AI and ML, follow a methodical workflow to develop sound solutions, use open source, off-the-shelf tools to develop, test, and deploy those solutions, and ensure that they protect the privacy of users. The specialization is designed for data science practitioners entering the field of artificial intelligence and will prepare learners for the CAIP certification exam. Your journey to CAIP Certification 1) Complete the Coursera Certified Artificial Intelligence Practitioner Professional Certificate 2) Review the CAIP AIP Exam Blueprint 3) Purchase your CAIP Exam Voucher 4) Register for your CAIP Exam

CertNexus Certified Artificial Intelligence Practitioner

Frequently Asked Questions

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Follow a Machine Learning Workflow

About this Course

What you will learn

Skills you will gain