Practical Machine Learning without Coding

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Practical Machine Learning without Coding

This course is part of No-Code Machine Learning and Data Science for Everyone Specialization

Instructor: LearnQuest Network

Included with

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3 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

3 hours to complete

Flexible schedule

Learn at your own pace

3 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

3 hours to complete

Flexible schedule

Learn at your own pace

Skills you'll gain

Tools you'll learn

Details to know

Shareable certificate

Add to your LinkedIn profile

See how employees at top companies are mastering in-demand skills

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Build your subject-matter expertise

This course is part of the No-Code Machine Learning and Data Science for Everyone 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 3 modules in this course

Learn to train and optimize common machine learning models, manage resource limitations, and streamline model building with no-code automation. Analyze output confidently with guided interpretation and error analytics.

Unlock practical machine learning for real-world impact—without ever touching code. In this module, gain hands-on experience building standard ML models on modern no-code platforms. Experiment efficiently by launching batch training jobs, automating performance reviews, and resolving errors confidently using intuitive guides. Simplify the art of hyperparameter tuning and learn to optimize model complexity for key business scenarios. Each lesson delivers actionable skills for fast career growth in today’s data-driven industries.

What's included

7 videos2 readings3 assignments

7 videos Total 12 minutes

Standard ML Models in No-Code Platforms 2 minutes
Launch batch model training jobs for quicker experimentation 2 minutes
Review automated performance metrics for rapid feedback 2 minutes
Diagnose errors using built-in troubleshooting guides 2 minutes
Conduct auto-tuning for key model parameters 2 minutes
Balance model complexity and accuracy with scenario-based optimization 2 minutes
Record tuning histories for compliance and reproducibility audits 2 minutes

2 readings Total 10 minutes

Action Story: Fixing Model Errors Before the Client Demo 5 minutes
Action Story: Tuning Under Pressure Before the Launch 5 minutes

3 assignments Total 62 minutes

Training and Evaluating Models with No-Code Systems 30 minutes
Coursera generated quiz 6 minutes
Graded Assignment 26 minutes

Take your machine learning skills to the next level with no-code tools built for scale. In this module, harness cloud-enabled features to process big data and deploy advanced models—without complexity. Build resilience into your workflows with automated backups, Geo specific model tuning, and integrated auditing to spot bias and keep models performing at their peak. Learn the frameworks that future-proof your work and ensure compliance as you grow.

What's included

7 videos1 reading3 assignments

7 videos Total 12 minutes

Advanced Algorithms and Automation for Scale 1 minute
Connect no-code tools to cloud resources for scalable computation 2 minutes
Manage big data workflows using partitioning and streaming features 2 minutes
Configure auto-backups to safeguard project continuity 2 minutes
Detect bias and fairness concerns with integrated audit features 2 minutes
Set automation for periodic retraining triggered by data changes 1 minute
Monitor model health with live diagnostic dashboards 2 minutes

1 reading Total 5 minutes

Action Story: Scaling Up Before the Product Launch 5 minutes

3 assignments Total 42 minutes

Building Scalable Models on Cloud No-Code Platforms 10 minutes
Auditability and Automation in ML Workflows 6 minutes
Coursera generated quiz 26 minutes

Bring machine learning models to life in real business environments—without a single line of code. This module shows how to deploy solutions quickly and reliably using no-code workflow editors and seamless API integrations. Learn to drive measurable impact, automate deployment, and foster ongoing improvement with strong communication and stakeholder engagement. Master the skills that transform ML prototypes into business-critical assets, clear resistance, and set the stage for success.

What's included

7 videos2 readings2 assignments

7 videos Total 12 minutes

Production Deployment and Integration 2 minutes
Publish models as live endpoints for real-time access 2 minutes
Connect output to business apps via pre-configured APIs 2 minutes
Automate deployment using drag-and-drop workflow editors 2 minutes
Demonstrate clear business impact with interactive ROI visualizations 1 minute
Create evidence-based communication plans for model launches 2 minutes
Manage feedback cycles with continuous improvement tracking 2 minutes

2 readings Total 10 minutes

Action Story: Deploying a Model Before the Executive Review 5 minutes
Action Story: Winning Support for the AI Rollout 5 minutes

2 assignments Total 36 minutes

Deploying Models and APIs from No-Code Workflows 10 minutes
Production Deployment and Integration 26 minutes

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.

Instructor

LearnQuest Network

LearnQuest

201 Courses 965,730 learners

Offered by

LearnQuest

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