SELF-PACED LEARNING
SELF-PACED LEARNING
Applied Data Science with Python
Master the tools and techniques used by data scientists every day.
Learn from industry experts as you build real-world machine learning models and take your Python skills to a professional level.
Master the tools and techniques used by data scientists every day.
Learn from industry experts as you build real-world machine learning models and take your Python skills to a professional level.
INDUSTRY-GRADE CONTENT
Course Length
5 Weeks
Course Length
5 Weeks
Enrollment
Start Anytime
Enrollment
Start Anytime
Self-Paced Online
Learn at your own pace
Self-Paced Online
Learn at your own pace
Time Commitment
2 - 4 hours per week
Time Commitment
2 - 4 hours per week
Course Overview
Course Overview
Advanced skills in Python is crucial for many data science roles. In this course, you will continue to build on the Python programming skills you acquired in the previous class by implementing machine learning using python libraries like TensorFlow, Py torch scikit-learn You will learn all the advanced Python libraries which are being used in the real world by data scientists. Data Science with Python training help you advance your career as a data scientist. Through a combination of theoretical concepts, real-world projects, and interactive exercises, participants will learn how to collect, clean, analyze, and visualize data and effectively communicate their findings
Advanced skills in Python is crucial for many data science roles. In this course, you will continue to build on the Python programming skills you acquired in the previous class by implementing machine learning using python libraries like TensorFlow, Py torch scikit-learn You will learn all the advanced Python libraries which are being used in the real world by data scientists. Data Science with Python training help you advance your career as a data scientist. Through a combination of theoretical concepts, real-world projects, and interactive exercises, participants will learn how to collect, clean, analyze, and visualize data and effectively communicate their findings
Self-paced
Structured learning
Take control of your education with a structured learning platform designed to deliver cutting-edge technical skills in consumable segments you can access anytime, anywhere.
AT A GLANCE
Self-Paced, Flexible Learning
Follow expert-architected paths from novice to specialist on your own terms. Access repeatable lectures and technical modules 24/7—anytime, anywhere, online or off.
24-7 Hands-On Labs
Access our cloud-based practice environments 24/7. Break things, fix them, and master industry-standard tools at your own pace
Certification-Ready Prep
Validate your expertise with unlimited practice assessments. Mirror the rigor and format of official professional exams to ensure you are 100% ready for exam day.
Intructor-Led (Live Project-Based Learning)
Self-paced
Structured learning
Take control of your education with a structured learning platform designed to deliver cutting-edge technical skills in consumable segments you can access anytime, anywhere.
AT A GLANCE
Self-Paced, Flexible Learning
Follow expert-architected paths from novice to specialist on your own terms. Access repeatable lectures and technical modules 24/7—anytime, anywhere, online or off.
24-7 Hands-On Labs
Access our cloud-based practice environments 24/7. Break things, fix them, and master industry-standard tools at your own pace
Certification-Ready Prep
Validate your expertise with unlimited practice assessments. Mirror the rigor and format of official professional exams to ensure you are 100% ready for exam day.
Intructor-Led (Live Project-Based Learning)
Course Outline
Course Outline
Introduction to Scikit-Learn
This module introduces Scikit-Learn, an essential machine learning library in Python. It covers its core features, including supervised and unsupervised learning algorithms, model training, and evaluation. Students explore Scikit-Learn's functionalities for classification, regression, clustering, and model evaluation, establishing a foundational understanding of machine learning with this powerful library.
Introduction to Scikit-Learn
This module introduces Scikit-Learn, an essential machine learning library in Python. It covers its core features, including supervised and unsupervised learning algorithms, model training, and evaluation. Students explore Scikit-Learn's functionalities for classification, regression, clustering, and model evaluation, establishing a foundational understanding of machine learning with this powerful library.
Machine Learning with Scikit-Learn
Machine Learning with Scikit-Learn
Advanced PyTorch Techniques and Applications
Advanced PyTorch Techniques and Applications
Introduction to Tensor Flow
Introduction to Tensor Flow
Deep Learning Fundamentals with Tensor Flow
Deep Learning Fundamentals with Tensor Flow
Convolutional Neural Networks (CNNs) with Tensor Flow
Convolutional Neural Networks (CNNs) with Tensor Flow
Recurrent Neural Networks (RNNs)
Recurrent Neural Networks (RNNs)
Introduction to PyTorch and Tensors
Introduction to PyTorch and Tensors
Deep Learning with PyTorch
Deep Learning with PyTorch
FIND THE RIGHT PATH FOR YOU
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Ready to land a job
you’ll love?
At MCIT, progress shows up when you do. We're here to guide you from where you are to where you deserve to be.
Apply today and get the learning and resources you need to help you prepare for a job in tech.
Ready to land a job
you’ll love?
At MCIT, progress shows up when you do. We're here to guide you from where you are to where you deserve to be.
Apply today and get the learning and resources you need to help you prepare for a job in tech.
Montreal College of Information Technology
200-1255 Robert-Bourassa Blvd.
Montreal, Quebec H3B 3B2
+1 514 312 2383
info@montrealcollege.ca