Predictive Modeling & Evaluation with Machine Learning
The module that connects Big Data Analytics, Visualization, and Statistics into real predictive models — using Linear Regression with Machine Learning in Python.
Turn statistics and visualization into models that actually forecast.
The Data Science Course series' main module connecting Big Data Analytics, Visualization, and Statistical concepts to create Predictive Models using Linear Regression with Machine Learning — done in Python. Empowers you with the Data Science skills to start making accurate forecasts and estimations with the data you have, in any functionality across any industry.
Those ready to move from analysis to prediction.
All those on a Data Science journey who have learnt Python for Big Data Analytics and Visualization, as well as statistical concepts, and now wish to move on to creating Machine Learning models for forecasting and prediction. It provides the basis for all advanced ML and AI model development and implementation.
Predictive Modeling is the core concept underlying Machine Learning.
This level of Ambeone's certification Data Science course in Dubai covers Predictive Modeling and Basic Machine Learning with Python, and starts you on the path toward Machine Learning and Artificial Intelligence. It's a creative and rewarding field, and it's here to stay — which is why we've designed a hands-on, practical curriculum for Managers, Decision Makers, Business Analysts, and future Data Analysts and Data Scientists.
Developing Predictive Models using Big Data Analytics is a fast-evolving phenomenon, just like the IT revolution was in the 90s. By applying statistical methods to massive amounts of data, data scientists can find trends, patterns, correlations, and outliers in their business of interest — translating directly into identifying opportunities and risks ahead of time, and making data-driven business decisions that improve efficiency, increase profits, mitigate risk, and open new markets.
This level builds on everything from earlier levels — data interpretation, data visualization, exploration, and statistical analysis — and uses it to create Predictive Modeling for different business applications using linear regression.
What this module covers.
- Correlation and Regression
- Linear Regression using Machine Learning Models
- Exploratory Data Analysis
- Simple and Multiple Regression case studies in Python
- Model Evaluation Parameters
- Examination of Residuals Plots
- Homoscedasticity and other error patterns
- Multicollinearity and Variance Inflation Factor (VIF)
Once you've mastered the topics in this level, you're ready to continue into Level VII — Advanced Machine Learning and AI with Python.
Approved since 2014
30+ years practitioner-led
100% in-person
Max 8 learners
Comprehensive Program in Data Science
Ambeone offers a discounted package covering all initial levels in the Data Science series with this level included, as the Comprehensive Program in Data Science — covering Statistics and Big Data Analytics & Visualization all the way up to Predictive Modeling with Python. Also available as a 5-day Intensive Boot Camp for international candidates and corporates.
Our recommended learning structure for the Data Science Series.
| Level | Course | |
|---|---|---|
| Level O – Base | AI Literacy & Productivity Courses | Click here |
| Level I | Descriptive Statistics, Data Interpretation, KPI | Click here |
| Level II | KPI Development and Measurement | Click here |
| Level II | Power BI for Business Analytics | Click here |
| Level IV | Advanced Data Mining & Manipulation with Python | Click here |
| Level V | Inferential & Predictive Statistics for AI and Data Science | Click here |
| Level VI | Predictive Modeling & Evaluation with Machine Learning | You are here |
| Level VII | Advance Machine Learning and AI with Python | Click here |
| Level VIII | Applied Analytics | Click here |
| Level IX | Neural Network & Unsupervised Learning for Advanced AI | Click here |
Common questions about this course.
Do I need to know Python before starting this course?
Yes — proficient skills in Python for big data analytics and visualization are a prerequisite, along with completing the Statistics level (Level V).
What if I haven't completed Statistics at Ambeone?
You can qualify by passing an examination demonstrating good understanding of statistics, since this course relies heavily on statistical theory.
What comes after this level?
Level VII — Advance Machine Learning and Artificial Intelligence with Python — builds directly on the predictive modeling skills taught here.
