Machine Learning with Qlik AutoML: No-Code Predictive Modeling — PickAClass
★ 4.5 (4) ⏱ 3h 📚 30 lessons

Machine Learning with Qlik AutoML: No-Code Predictive Modeling

Build and deploy predictive models for business insights using automated machine learning tools without writing a single line of code.

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About this course

Machine learning is no longer reserved for expert coders or mathematicians. You can now leverage the power of advanced algorithms to solve business problems and predict future outcomes using intuitive, automated tools. This course transforms you from a beginner into a confident user of automated machine learning. You will learn how to navigate the entire predictive lifecycle, from preparing your datasets to interpreting complex model results, all through written explanations and practical examples. What you'll learn: - Understand core machine learning terminology and foundational concepts. - Navigate the automated machine learning workflow from data preparation to prediction. - Apply feature engineering and selection techniques to improve model quality. - Evaluate model performance using key metrics like accuracy, precision, and recall. - Identify and mitigate potential bias in automated models to ensure ethical AI practices. - Deploy trained models to generate real-world business predictions. The course begins with essential definitions and an overview of the machine learning lifecycle. You will then progress through the technical stages of configuring experiments, refining models, and interpreting the drivers behind your data's behavior. This course is designed for beginners, data analysts, and business professionals who want to leverage machine learning without learning complex programming languages or advanced statistics. No prior coding experience is required. Start your journey into automated machine learning today.

Course contents

6 modules · 30 lessons · 3h

1 Introduction to Automated Machine Learning
Establish foundational knowledge and understand the AutoML environment.
5 lessons · 30 min
  1. What is Machine Learning?
    Understand ML as a way to find patterns in data to make predictions without explicit programming.
    6 min
  2. The Vocabulary of ML
    Define key terms like features, targets, training sets, and testing sets.
    6 min
  3. The Machine Learning Lifecycle
    Walk through the stages from business problem definition to model deployment.
    6 min
  4. Introduction to Qlik AutoML
    Navigate the Qlik Cloud interface where automated ML experiments happen.
    6 min
  5. Types of ML Problems
    Distinguish between classification and regression in a business context.
    6 min
2 Data Preparation & Experiment Setup
Learn how to format data and initiate an AutoML experiment.
5 lessons · 30 min
  1. Preparing Your Dataset
    Learn the requirements for clean, tabular data suitable for Qlik AutoML.
    6 min
  2. Identifying the Target Variable
    Choose the specific outcome you want the model to predict.
    6 min
  3. Configuring Your First Experiment
    Set up the initial parameters and upload data to start an automated run.
    6 min
  4. Data Profiling in Qlik
    Use built-in tools to check data distributions and potential issues.
    6 min
  5. Handling Missing Values
    Understand how AutoML automatically manages nulls and gaps in your data.
    6 min
3 Feature Engineering & Model Refining
Improve model performance through smart data manipulation.
5 lessons · 30 min
  1. Basics of Feature Engineering
    Create new input variables that help the model learn better patterns.
    6 min
  2. Transforming Categorical Data
    Understand how text-based categories are converted for machine processing.
    6 min
  3. Analyzing Feature Importance
    Identify which columns have the most impact on your target prediction.
    6 min
  4. The Art of Feature Selection
    Remove noisy or redundant data to streamline and improve your model.
    6 min
  5. Iterating for Quality
    Refine the model by adjusting features and re-running the experiment.
    6 min
4 Evaluating Model Performance
Interpret metrics to determine if a model is ready for business use.
5 lessons · 30 min
  1. The AutoML Leaderboard
    Compare different algorithms automatically trained by Qlik.
    6 min
  2. Understanding Accuracy
    Learn when simple accuracy is a good metric and when it is misleading.
    6 min
  3. Precision and Recall
    Balance the cost of false positives versus false negatives.
    6 min
  4. The F1-Score and AUC
    Use advanced metrics to get a holistic view of model health.
    6 min
  5. Using the Confusion Matrix
    Visualize exactly where the model is making mistakes.
    6 min
5 Interpreting Results & Ethical AI
Explain model decisions and ensure fairness.
5 lessons · 30 min
  1. Global vs. Local Interpretability
    Distinguish between overall model drivers and individual prediction reasons.
    6 min
  2. Interpreting Prediction Drivers
    Use SHAP values to explain why a specific prediction was made.
    6 min
  3. Identifying Bias in Data
    Spot historical biases that could lead to unfair model outcomes.
    6 min
  4. Mitigating Bias & Ethical AI
    Apply techniques to ensure models are fair and ethically sound.
    6 min
  5. Communicating Insights
    Translate technical model results into actionable business stories.
    6 min
6 Deployment & Real-World Application
Move from a trained model to generating actual business value.
5 lessons · 30 min
  1. Deploying Your Model
    Promote a successful experiment to a production-ready deployment.
    6 min
  2. Generating Batch Predictions
    Apply your model to new datasets to predict future outcomes.
    6 min
  3. Real-Time Prediction Use Cases
    Explore how models can provide instant feedback in business apps.
    6 min
  4. Integrating with Qlik Sense
    Visualize predictions alongside historical data in dashboards.
    6 min
  5. Monitoring & Maintenance
    Keep an eye on model performance over time to prevent 'drift'.
    6 min
Final project

The Customer Churn Predictor

You will take a raw dataset of customer behavior, prepare it for Qlik AutoML, build a model to predict who will leave the service, evaluate its fairness, and deploy it to generate a list of high-risk customers.

What you'll get

  • 📜 Certificate of completion
    Add it to your LinkedIn profile
  • 💬 Personal AI tutor
    Stuck on a lesson? Ask your built-in tutor anything, any time.
  • ♾️ Lifetime access
    Come back anytime, no expiry
  • 📱 Phone or computer
    Works anywhere, any device
  • 💸 14-day refund
    No questions asked
  • ⚡ Short & focused
    3h of practical content

Certificate of completion

Every course you complete on PickAClass issues a credential like this — original, with its own code, verifiable by URL, and detailed about what was actually demonstrated.

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PickAClass
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Certificate of Mastery
This certifies that
Name Surname
has successfully demonstrated mastery of
Machine Learning with Qlik AutoML: No-Code Predictive Modeling
Skills demonstrated
✓
Behavioral pattern analysis
Foundational
1.2 hrs
✓
Decision-architecture frameworks
Proficient
1.4 hrs
✓
A/B test design
Proficient
1.7 hrs
✓
Behavioral copywriting
Advanced
1.9 hrs
P
PickAClass — Name Surname
Machine Learning with Qlik AutoML: No-Code Predictive Modeling
Page 2 of 2
Performance detail
Coursework summary
Lessons completed 14 / 14
Practice questions 26 / 28
Assignments submitted 4 (avg 4.5 / 5)
Capstone project Reviewed — 4.6 / 5
Total practice 6.2 hrs
Performance benchmark
Cohort rank Top 12% of 1,625
Time to completion 11 days (median: 22)
Mastery score 91 / 100
Practice-question score 94%
Skill verification Verified Skill Path
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pickaclass.com/certificates/PCC-2026-X4F7-AP19
Issued under the academic standards of PickAClass. Skill levels reflect assessed performance against the course's competency rubric. This is an original credential of this platform.

Reviews (4)

Adrián Morales ES Verified learner
★ 4 · October 10, 2026

This exceeded my expectations. The lessons flowed logically and the real-world applications were spot on. Great job!

ناصر بن علي الخروصي OM
★ 5 · August 18, 2026

This course exceeded my expectations. The real-world applications discussed are incredibly useful. Great job!

Camila González MX Verified learner
★ 5 · July 22, 2026

Wow, what a fantastic learning experience. The structure was logical, and I felt like I learned so much in a short time. Definitely recommend.

Jumoke Alabi NG
★ 4 · July 8, 2026

Fantastic learning experience. The pace was perfect, and the examples really solidified the concepts. Big thumbs up!

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