About this Course

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Shareable Certificate

Earn a Certificate upon completion

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Flexible deadlines

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Advanced Level

Approx. 6 hours to complete

English

Subtitles: English

Skills you will gain

Data ScienceInformation EngineeringArtificial Intelligence (AI)Machine LearningPython Programming

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Advanced Level

Approx. 6 hours to complete

English

Subtitles: English

Offered by

IBM logo

IBM

Syllabus - What you will learn from this course

Week
1

Week 1

4 hours to complete

Model Evaluation and Performance Metrics

4 hours to complete
6 videos (Total 18 min), 19 readings, 6 quizzes
6 videos
Evaluation Metrics2m
Introduction to Predictive Linear and Logistic Regression3m
Linear Models4m
Watson Natural Language Understanding Service Overview3m
Case Study Introduction1m
19 readings
Evaluation metrics: Through the eyes of our Working Example3m
Evaluation Metrics3m
Regression metrics5m
Classification metrics10m
Multi-class and multi-label metrics3m
Model performance: Through the eyes of our Working Example3m
Generalizing well to unseen data3m
Model plots, bias, variance4m
Relating the evaluation metric to a business metric4m
Linear models: Through the eyes of our Working Example3m
Generalized linear models5m
Linear and logistic regression5m
Regularized regression3m
Stochastic gradient descent classifier3m
Watson Natural Language Understanding: Through the eyes of our Working Example3m
Watson Developer Cloud Python SDK10m
Performance and business metrics: Through the eyes of our Working Example3m
Getting started with performance and business metrics case study (hands-on)2h
Summary/Review10m
6 practice exercises
Check for Understanding2m
Check for Understanding2m
Check for Understanding2m
Check for Understanding2m
Check for Understanding2m
End of Module Quiz10m
Week
2

Week 2

3 hours to complete

Building Machine Learning and Deep Learning Models

3 hours to complete
5 videos (Total 15 min), 14 readings, 5 quizzes
5 videos
Introduction to Tree Based Methods2m
Neural Networks2m
Introduction to neural networks4m
IBM Watson Visual Recognition Overview2m
14 readings
Tree-based methods: Through the eyes of our Working Example3m
Decision trees4m
Bagging and Random forests4m
Boosting2m
Ensemble learning4m
Neural networks: Through the eyes of our Working Example3m
Multilayer perceptron (MLP)4m
Neural network architectures4m
On interpretability2m
Watson Visual Recognition: Through the eyes of our Working Example3m
Watson Developer Cloud Python SDK10m
TensorFlow: Through the eyes of our Working Example3m
Getting started with Convolutional neural networks and TensorFlow (hands-on)2h
Summary/Review10m
5 practice exercises
Check for Understanding2m
Check for Understanding2m
Check for Understanding2m
Check for Understanding2m
End of Module Quiz10m

About the IBM AI Enterprise Workflow Specialization

This six course specialization is designed to prepare you to take the certification examination for IBM AI Enterprise Workflow V1 Data Science Specialist. IBM AI Enterprise Workflow is a comprehensive, end-to-end process that enables data scientists to build AI solutions, starting with business priorities and working through to taking AI into production. The learning aims to elevate the skills of practicing data scientists by explicitly connecting business priorities to technical implementations, connecting machine learning to specialized AI use cases such as visual recognition and NLP, and connecting Python to IBM Cloud technologies. The videos, readings, and case studies in these courses are designed to guide you through your work as a data scientist at a hypothetical streaming media company. Throughout this specialization, the focus will be on the practice of data science in large, modern enterprises. You will be guided through the use of enterprise-class tools on the IBM Cloud, tools that you will use to create, deploy and test machine learning models. Your favorite open source tools, such a Jupyter notebooks and Python libraries will be used extensively for data preparation and building models. Models will be deployed on the IBM Cloud using IBM Watson tooling that works seamlessly with open source tools. After successfully completing this specialization, you will be ready to take the official IBM certification examination for the IBM AI Enterprise Workflow....
IBM AI Enterprise Workflow

Frequently Asked Questions

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • 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.

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