

Applied Data Science with Python
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.
Talk to an Advisor
Talk to an Advisor
36 hours
Schedule : Mon - Wed - Thu
6 PM - 9 PM
Duration
36 hours
Schedule : Mon - Wed - Thu
6 PM - 9 PM
Duration
Modular thinking,
Programming basics,
Algorithimic thinking,
Problem solving
Debugging
Skills Gained
Modular thinking,
Programming basics,
Algorithimic thinking,
Problem solving
Debugging
Skills Gained
Instructor led or
Self paced
Mentor guided
Online & Hybrid
learning
Learning Methodology
Instructor led or
Self paced
Mentor guided
Online & Hybrid
learning
Learning Methodology
Program Overview
Program 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
Key Benefits
Key Benefits

Get trained by industry Experts
Our courses are delivered by professionals with years of experience having learned first-hand the best, in-demand techniques, concepts, and latest tools.
Get trained by industry Experts
Our courses are delivered by professionals with years of experience having learned first-hand the best, in-demand techniques, concepts, and latest tools.
Official Certification curriculum
Our curriculum is kept up to date with the latest official Certification syllabus and making you getting ready to take the exam.
Official Certification curriculum
Our curriculum is kept up to date with the latest official Certification syllabus and making you getting ready to take the exam.
Tax Credit
Claim up to 25% of tuition fees and education tax credit from your taxes.
Tax Credit
Claim up to 25% of tuition fees and education tax credit from your taxes.
Discount on Certification Voucher
Upto 50 percent discount voucher will be provided.
Discount on Certification Voucher
Upto 50 percent discount voucher will be provided.
24/7 Lab access
Our students have access to their labs and course materials at any hour of the day to maximize their learning potential and guarantee success.
24/7 Lab access
Our students have access to their labs and course materials at any hour of the day to maximize their learning potential and guarantee success.
Course Outline
Course Outline
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Introduction to Scikit-Learn
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Machine Learning with Scikit-Learn
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Introduction to Tensor Flow
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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
Advanced PyTorch Techniques and Applications
Advanced PyTorch Techniques and Applications
Introduction to Scikit-Learn
Machine Learning with Scikit-Learn
Introduction to Tensor Flow
Deep Learning Fundamentals with Tensor Flow
Convolutional Neural Networks (CNNs) with Tensor Flow
Recurrent Neural Networks (RNNs)
Introduction to PyTorch and Tensors
Deep Learning with PyTorch
Advanced PyTorch Techniques and Applications
Skills gained
Skills gained
Deep Learning Fundamentals
Model Implementation
Tensor Manipulation
Model Training and Optimization
Model Deployment
Deep Learning Fundamentals
Model Implementation
Tensor Manipulation
Model Training and Optimization
Model Deployment
Instructor Spotlight
Instructor Spotlight
Connect with our instructors at an event . Build your intelligent network .
Connect with our instructors at an event . Build your intelligent network .
Michel Chamoun
Data Science & Business Analyst
Michel is a highly skilled developer and consultant with expertise in AI, data analysis, and process optimization. As a developer in the GenAI team, he built proof-of-concepts leveraging chatGPT's natural language understanding capabilities and implemented AI modules on Microsoft Azure. As a consultant in the strategy and operations team, he designed algorithms for user access profiling.
Iraj Hedayati
Data Engineering Lead
Iraj Hedayati is a seasoned Data Engineer with over a decade of experience designing and scaling data infrastructure at high-growth tech companies. He currently works as a consultant with Apple, specializing in distributed systems, Spark, and backend development. Iraj teaches Data Engineering courses focused on real-world applications in big data processing, cloud infrastructure, and modern data pipelines. His industry background includes leading large-scale data migrations, optimizing cloud costs, and building end-to-end systems for data ingestion and analytics.
Mojtaba Faramarzi
Applied Research Scientist
Mojtaba holds a Ph.D. in Machine Learning from the University of Montreal–Mila, along with two master’s degrees in Software Engineering from Concordia University and Machine Learning from the University of Montreal. He brings extensive experience in both academia and industry, having taught a range of computer science and software engineering courses with a focus on practical AI applications. He has also worked in leading tech companies, including Amazon, Microsoft, SAP, and Ericsson. Passionate about student engagement and interdisciplinary learning, he is committed to fostering critical thinking and innovation in the classroom.
Mojtaba Ghasemi
Senior Data Scientist
A results-driven Data Scientist with a Ph.D. in Biomedical Engineering, specializing in advanced analytics, predictive modeling, and machine learning. With 5 years of experience and currently working as a Senior Data Scientist, I excel at translating complex analytical insights for non-technical audiences and leading cross-functional teams to deliver impactful business solutions
Michel Chamoun
Data Science & Business Analyst
Michel is a highly skilled developer and consultant with expertise in AI, data analysis, and process optimization. As a developer in the GenAI team, he built proof-of-concepts leveraging chatGPT's natural language understanding capabilities and implemented AI modules on Microsoft Azure. As a consultant in the strategy and operations team, he designed algorithms for user access profiling.
Iraj Hedayati
Data Engineering Lead
Iraj Hedayati is a seasoned Data Engineer with over a decade of experience designing and scaling data infrastructure at high-growth tech companies. He currently works as a consultant with Apple, specializing in distributed systems, Spark, and backend development. Iraj teaches Data Engineering courses focused on real-world applications in big data processing, cloud infrastructure, and modern data pipelines. His industry background includes leading large-scale data migrations, optimizing cloud costs, and building end-to-end systems for data ingestion and analytics.
Mojtaba Faramarzi
Applied Research Scientist
Mojtaba holds a Ph.D. in Machine Learning from the University of Montreal–Mila, along with two master’s degrees in Software Engineering from Concordia University and Machine Learning from the University of Montreal. He brings extensive experience in both academia and industry, having taught a range of computer science and software engineering courses with a focus on practical AI applications. He has also worked in leading tech companies, including Amazon, Microsoft, SAP, and Ericsson. Passionate about student engagement and interdisciplinary learning, he is committed to fostering critical thinking and innovation in the classroom.
Mojtaba Ghasemi
Senior Data Scientist
A results-driven Data Scientist with a Ph.D. in Biomedical Engineering, specializing in advanced analytics, predictive modeling, and machine learning. With 5 years of experience and currently working as a Senior Data Scientist, I excel at translating complex analytical insights for non-technical audiences and leading cross-functional teams to deliver impactful business solutions
Eligibility Criteria
Eligibility Criteria
Learners need to possess an undergraduate degree or a high school diploma. No need of any professional experience is required as this is the fundamental course.
Possess an undergraduate degree or a high school diploma.
Prerequisites
Statistics, Machine Learning and Python Programming are prerequisites for this certification course.
Upcoming sessions & Schedule
Upcoming sessions
& Schedule
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FAQs
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Montreal College of Information Technology
Collège des technologies de l’information de Montréal
200-1255 Robert-Bourassa Blvd.
Montreal, Quebec H3B 3B2
+1 514 312 2383


Montreal College of Information Technology
Collège des technologies de l’information de Montréal
200-1255 Robert-Bourassa Blvd.
Montreal, Quebec H3B 3B2
+1 514 405 6874


Montreal College of Information Technology
Collège des technologies de l’information de Montréal
200-1255 Robert-Bourassa Blvd.
Montreal, Quebec H3B 3B2
+1 514 405 6874