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DV-CIS306.AP1
AI, Machine Learning and Data Science
Intermediate Self-paced · 1 year access
10 Hands-On LiveLabs
Practice real IT tasks in guided environments.
- Real environments
- Auto-graded
- No installation
01 / Lessons & labs
See exactly what you will learn and practice
Lessons
7 Interactive Lessons · 62 topics01 Introduction to Analytics 9 topics +
- What’s in a Name?
- Why the Sudden Popularity of Analytics and Data Science?
- The Application Areas of Analytics
- The Main Challenges of Analytics
- A Longitudinal View of Analytics
- A Simple Taxonomy for Analytics
- The Cutting Edge of Analytics: IBM Watson
- Summary
- References
02 Introduction to Predictive Analytics and Data Mining 8 topics · 2 LiveLab +
- What Is Data Mining?
- What Data Mining Is Not
- The Most Common Data Mining Applications
- What Kinds of Patterns Can Data Mining Discover?
- Popular Data Mining Tools
- The Dark Side of Data Mining: Privacy Concerns
- Summary
- References
2 LiveLab in this lesson — see the labs panel →
03 Standardized Processes for Predictive Analytics 8 topics +
- The Knowledge Discovery in Databases (KDD) Process
- Cross-Industry Standard Process for Data Mining (CRISP-DM)
- SEMMA
- SEMMA Versus CRISP-DM
- Six Sigma for Data Mining
- Which Methodology Is Best?
- Summary
- References
04 Data and Methods for Predictive Analytics 13 topics · 1 LiveLab +
- The Nature of Data in Data Analytics
- Preprocessing of Data for Analytics
- Data Mining Methods
- Prediction
- Classification
- Decision Trees
- Cluster Analysis for Data Mining
- k-Means Clustering Algorithm
- Association
- Apriori Algorithm
- Data Mining and Predictive Analytics Misconceptions and Realities
- Summary
- References
1 LiveLab in this lesson — see the labs panel →
05 Algorithms for Predictive Analytics 10 topics · 4 LiveLab +
- Naive Bayes
- Nearest Neighbor
- Similarity Measure: The Distance Metric
- Artificial Neural Networks
- Support Vector Machines
- Linear Regression
- Logistic Regression
- Time-Series Forecasting
- Summary
- References
4 LiveLab in this lesson — see the labs panel →
06 Advanced Topics in Predictive Modeling 6 topics · 1 LiveLab +
- Model Ensembles
- Bias–Variance Trade-off in Predictive Analytics
- Imbalanced Data Problems in Predictive Analytics
- Explainability of Machine Learning Models for Predictive Analytics
- Summary
- References
1 LiveLab in this lesson — see the labs panel →
07 Text Analytics, Topic Modeling, and Sentiment Analysis 8 topics · 2 LiveLab +
- Natural Language Processing
- Text Mining Applications
- The Text Mining Process
- Text Mining Tools
- Topic Modeling
- Sentiment Analysis
- Summary
- References
2 LiveLab in this lesson — see the labs panel →
Hands-On Labs Our edge
10 LiveLabs- Creating a Decision Tree in Python
- Creating a Decision Tree in KNIME
- Running k-Means Clustering Algorithm in KNIME
- Using the k-Nearest Neighbor Algorithm
- Using ANN and SVM for Prediction Type Analytics Problems
- Implementing Linear Regression in Python
- Implementing Linear Regression Model in KNIME
- Showcasing Better Practices With a Customer Churn Analysis
- Performing Topic Modeling
- Performing Sentiment Analysis
Labs run in your browser — nothing to install.
02 / FAQs
Questions before you start
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