Data Science and AI using Python Training in Ontario

Data Science and AI using Python Training in Ontario, Canada

Participants will learn how to analyze, visualize, and model data, and apply machine learning algorithms to solve real-world problems.

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Data Science and AI using Python Training is a professional training program delivered by ProgNXT in Ontario, Canada. ProgNXT, a globally recognized corporate training provider in 55+ countries, offers this Data Science and AI using Python Training course with hands-on, instructor-led sessions. This course provides a thorough grounding in Data Science and Artificial Intelligence (AI) using Python. Participants will learn how to analyze,...

Expert Panel

Designed by the ProgNXT AI & Data Science Expert Panel, specializing in Generative AI, Machine Learning, and ChatGPT applications

ProgNXT AI & Data Science Expert Panel

Course Code: VKI74
21 Hrs
Last Updated: April 2026

Course Rating5/5

This course provides a thorough grounding in Data Science and Artificial Intelligence (AI) using Python. Participants will learn how to analyze, visualize, and model data, and apply machine learning algorithms to solve real-world problems. The course blends theoretical concepts with hands-on practice, covering everything from data preprocessing to deploying machine learning models.

Welcome to the official Data Science and AI using Python Training certification program in Ontario, Canada. This comprehensive training is designed to elevate your professional skills and provide you with practical, industry-relevant knowledge locally. As a globally recognized corporate training provider operating in 55+ countries, ProgNXT ensures that our curriculum meets the highest standards of excellence.

Whether you are looking to upskill your team or advance your personal career, our expert-led sessions will guide you through the core concepts of this domain. Upon successful completion of the 21 Hrs program, participants will receive a globally accepted certification, demonstrating their proficiency and readiness to tackle complex challenges in the field.

Basic understanding of Python programming
Fundamental knowledge of statistics and linear algebra is helpful
Familiarity with Jupyter Notebooks and Python IDEs
No prior experience in machine learning or AI is required

By the end of the course, participants will be able to:

Understand the data science workflow and tools
Use Python for data manipulation, visualization, and statistical analysis
Build and evaluate machine learning models using Scikit-learn
Apply AI techniques like deep learning using TensorFlow or PyTorch
Handle real-world datasets and deliver actionable insights
Deploy trained models using basic APIs or cloud platforms

Python for Data Science
Data preprocessing and visualization
Statistical analysis and hypothesis testing
Supervised and unsupervised machine learning
Deep learning with neural networks
Model evaluation, optimization, and deployment
Working with libraries: NumPy, Pandas, Matplotlib, Scikit-learn, TensorFlow/Keras

Python programming for data tasks
Data wrangling, cleaning, and visualization
Machine learning model building and evaluation
Deep learning basics
Real-world data analysis and insight generation
Final mini-capstone project

Participants who attend all sessions and successfully complete the course assessments will receive a ProgNXT Certificate of Completion.

Introduction to Python and Data Science

Overview of Data Science and AI
Setting up Python (Anaconda, Jupyter)
Python basics: data types, loops, functions
Working with NumPy and Pandas

Data Visualization & Statistics

Data cleaning and wrangling
Visualization using Matplotlib and Seaborn
Statistical analysis and feature engineering
Correlation and causation

Machine Learning Foundations

Introduction to machine learning
Supervised vs. unsupervised learning
Regression and classification algorithms (Linear, Logistic, KNN)
Model training, testing, and evaluation (metrics: accuracy, precision, recall)

AI and Deep Learning Concepts

Neural networks and perceptrons
Introduction to TensorFlow/Keras
Building a simple deep learning model
Overfitting, regularization, and dropout

Hands-on Exercises

Summary and Conclusion

Slide decks and PDF notes
Sample datasets for exercises
Access to code repositories
Recommended readings and cheat sheets

Hands-on Labs & Assignments
Quizzes & Participation
Peer Feedback & Review

ProgNXT Certificate of Completion will be awarded to participants who successfully complete the course and assessments.

Data Science and AI using Python Training Events in ontario

Online Events

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More Upcoming Session Dates

October 2026

🌐 Online Instructor-Led

22nd Oct 2026→24th Oct 2026

📍 Ontario, Canada

24th Oct 2026→26th Oct 2026

November 2026

📍 Ontario, Canada

2nd Nov 2026→4th Nov 2026

🌐 Online Instructor-Led

7th Nov 2026→9th Nov 2026

📍 Ontario, Canada

18th Nov 2026→20th Nov 2026

🌐 Online Instructor-Led

23rd Nov 2026→25th Nov 2026

December 2026

🌐 Online Instructor-Led

4th Dec 2026→6th Dec 2026

📍 Ontario, Canada

11th Dec 2026→13th Dec 2026

📍 Ontario, Canada

19th Dec 2026→21st Dec 2026

🌐 Online Instructor-Led

28th Dec 2026→30th Dec 2026

Events for other courses in Ontario, Canada

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Data Science and AI using Python Training in Ontario