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Data science course in Canada

5 ( 1410 Learners)

Get Your Dream Job With Our Data science course in Canada

30+ Hrs

Hands On Training

Lifetime Access

Updated Content

Customizable

Learning Paths

Industry Expert

Mentors

Projects

Advanced Interactive

Upcoming Live Online Classes

Course Price

119
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Data Science Course Canada - Course Overview

Data Science is a collection of statistical, data analysis, and machine learning approaches for extracting and analyzing large amounts of structured and unstructured data. A Data Scientist is a researcher tasked with preparing large volumes of big data for analysis, using complex quantitative algorithms to organize and synthesize the data, and presenting the findings to senior management through engaging visualizations. A Data Scientist improves business decision-making by speeding up the process and giving it more direction.

In today's data-driven world, a data science course in Canada can help you prepare for the growing demand for Data Science skills and technologies across all industries. In the subject of data science, there are numerous job opportunities, and this curriculum is one of the most comprehensive in the business today. This training in Canada is tailored to both data experts and beginners interested in pursuing a career in this fast-growing field. This course will provide students with the necessary logical and applicable programming skills to create database models. They will be able to solve issues and effectively convey solutions using elementary machine learning methods such as K-Means Clustering, Decision Trees, and Random Forest.. Enroll now to get the most out of your Data Science certification course in Canada

Data science course in Canada Prerequisites

To apply for the Data science course in Canada, you need to either:

  • You need to have a good foundation in mathematical concepts like linear algebra, calculus, probability and statistics
  • You need to know at least one programming language like Python or R. You need to have a good understanding of OOPs concepts, algorithms, and data structures.
  • You need to have some basic data analysis and data visualisation skills.

Data Science Course Canada - Course Content

We at HKR trainings provides an optimized Data Science course structure that helps the individual to gain the concepts easily. Now let's explore each module one after the other.

In this module, you are going to learn about the various Data Science concepts, as follows:

  • Introduction to Data Science, Importance of data science, applications, lifecycle, and components.
  • Big data Hadoop, machine learning and deep learning
  • Introduction to R programming and R studio.
  • Introduction to data exploration
  • Importing and exporting data to and from external sources
  • Data exploratory analysis
  • Data Frames, factors, loops, operators, conditional and looping statements, user-defined functions and data types, etc.
  • Introduction to data manipulation
  • Introduction to dplyr package
  • Briefing about functions and combining different features with the pipe operator
  • Implementing SQL operations with sqldf.
  • Introduction to data visualization
  • Explaining different graphs functions and it's implementations
  • Multivariate analysis with geom_boxplot
  • Univariate analysis with a barplot
  • Creation of barplots
  • Visualization with Plotly
  • Working with themes and coordinates to present graphs more visually and clearly.
  • Geographic visualization with ggmap() and building applications with shinyR.
  • Need for statistics
  • Categories of statistics
  • Correlation and covariance, standardization, normalization, normal distribution, chi-square testing, ANOVA, and binary distribution.
  • Introduction to machine learning, linear regression, predictive modeling, formulas, assumptions, and building a simple linear model
  • Introduction to logistic regression
  • Comparison of different types of regressions.
  • Confusion matrix the accuracy of a model, threshold evaluation with ROCR, and understanding qqnorm() and qqline()
  • Building linear models with multiple independent variables.
  • Introduction to logistic regression
  • Concepts of logistic regression
  • Building a simple binomial model
  • Finding out the right threshold using the ROC plot
  • Real-time applications of logistic regression.
  • Classification and it's techniques
  • Introduction to decision trees, algorithm and building a decision tree in R
  • Confusion matrix, regression trees vs. classification
  • trees Introduction to bagging
  • Random Forest and its implementation in R
  • Naive Bayes and it's computing possibilities
  • Concepts of Impurity function, Entropy, Gini index, and Information gain for the right split of node
  • Overfitting, pruning basics, finding out the correct number of trees, and evaluating performance metrics.
  • Clustering, types and use cases
  • Introduction to unsupervised learning
  • Feature extraction, clustering algorithm, and k-means clustering algorithm
  • Briefing about k-means and its implementation
  • Explaining the Principal Component Analysis (PCA) in detail and implementing PCA in R
  • Introduction to association rule mining, advantages, types, measuring the association
  • rule mining and implementation.
  • Introduction to recommendation engines
  • How are recommendation engines implemented in R?
  • Recommendation engines use cases. Summary
  • AI and deep learning
  • Fundamental of Artificial Neural Networks
  • Tensor Flow
  • Computational frameworks for building AI models
  • Fundamental of tensorflow and working it with R
  • What is a time series?
  • Techniques, applications, and components of the time series
  • ARIMA model
  • Time series in R, sentiment analysis in R (Twitter sentiment analysis), and text analysis
  • What is the Bayes theorem?, Naïve Bayes Classifier?
  • How Naive Bayes classifier works and classifier building in Scikit-Learn.
  • classification model using Naïve Bayes and the zero probability problem
  • Introduction to text mining, use cases, and understanding and manipulating the text with 'tm' and 'stringR'.
  • Text mining algorithms and the quantification of the text
  • TF-IDF and after TF-IDF

Data science project

Project 1
Color Detection

In this project we will create an application that will detect the selected color from an image. For developing this application w.....e need to label data of the familiar colors to us and the find out which color has the similarity to the color value in the selected image.  Read more

Project 2
Detection Of Brain Tumor

In this project we will be creating an application that will detect the brain tumor with the help of the datasets gathered from th.....e MRI Scan. In this way convolution neural networks can be trained from the scratch for detecting brain tumors. Read more

Project 3
Recognition Of Speech Emotion

In this project we will be creating an application for speech emotion recognition with the help of a number of libraries Librosa, .....SER, etc. Although it is a tough project, we will be creating an MLPClassifier for this model. Read more

Project 4
Fake News Detection App

In this project, you will create an application that will determine the legitimacy of the information. Fake news spreads very quic.....kly by some unauthorised person creating issues for others, which can sometimes lead to violence. Using the Data Science concepts you have learnt in the Data Science training, you can create a fake news detection application to identify the fake news. Read more

Data Science Course London Options

LIVE ONLINE TRAINING
  • Interactive sessions
  • Learn by doing
  • Instant doubt resolution
  • Expert's Guidance
  • Industry-ready skills

299

Pay installments with no cost EMI

1:1 LIVE ONLINE TRAINING
  • Exclusive training
  • Flexible timing
  • Personalized curriculum
  • Hands-on sessions
  • Simplified Learning

Exclusive learning from industry experts

699

Pay installments with no cost EMI

SELF-PACED E-LEARNING
  • Skill up easily
  • Learn in no hurry
  • Less expensive
  • Unlimited access
  • Convenient

Hone your skills from anywhere at anytime

119

Pay installments with no cost EMI

Data science course in Canada Corporate Training
Employee and Team Training Solutions

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Our Learners
Ravi Kukkala

Ravi Kukkala

SAP Ariba Technical Consultant

5
The SAP Ariba procurement training was spot on! It covered all aspects of the procurement process, from sourcing to contract management. The real-world scenarios and case studies provided practical insights. I'm confident in my ability to streamline procurement operations with SAP Ariba.
Soumya Kakkar

Soumya Kakkar

SAP Ariba Functional Consultant

5
The flexibility of the SAP Ariba online training was a game-changer. I could learn at my own pace and revisit the materials as needed. The instructor's support was excellent, and the online resources were comprehensive. This training has significantly enhanced my skills in procurement and sourcing
Kalyani

Kalyani

Sap Ariba Consultant | TCS

5
The SAP Ariba training was exceptional! The instructor was knowledgeable and patient, explaining complex concepts in a clear and concise manner. The hands-on exercises were invaluable in solidifying my understanding. I highly recommend this training for anyone looking to master SAP Ariba.
Data Science online Course in Canada - Objectives

The following list of things can be learned or explored during the data science course in Canada. They are:

  • Collaborate with a variety of data production sources.
  • Create a Customer Sentiment Analysis using Text Mining.
  • Use various tools and strategies to analyze organized and unstructured data.
  • Learn the difference between descriptive and predictive analytics.
  • For business decisions, use data-driven, machine learning methodologies.
  • Create models that can be used on a daily basis.
  • To make proactive business decisions, use forecasting.
  • To make data easier to grasp, use Data Concepts.

The Data Science training Certification offered in Canada was designed for professionals with and without work experience in any of the profiles below: 

  • IT Professionals
  • Analytics Managers
  • Business Analysts
  • Banking and Finance Professionals
  • Marketing Managers
  • Supply Chain Network Managers
  • Beginners or Recent Graduates in Bachelors or Master’s Degree

Any learner who wants to get the most out of HKR trainings Data Scientist Course in Canada should have the following skills:

  • A fundamental understanding of statistics and related principles is required.
  • At least one of the top/relevant programming languages is required.

To start with this Data Science training, you need to either click on the Enrol Now icon at the top of the screen, or contact us at our customer care number, or just enter your details in the pop-up and submit it. Our Team will contact you as soon as possible and give you more information regarding the training process.

Immediately after the successful completion of the course which is accompanied by the real time projects task and assignments, HKR trainings offers you the course completion certificate. This certification differentiates you from the other non-certified peers and also helps to get a job in any company in Canada very quickly.

The Data Science certified professionals at HKR trainings in Canada deliver the lectures to the individuals to unleash their abilities in this technology.

The benefits you can gain upon the completion of the certification are , you will be given higher preference for competitive jobs related to analytics.

The Data Science certified professionals at HKR trainings in Canada deliver the lectures to the individuals to unleash their abilities in this technology.

Yes! Right from the first day of your Data Science training, our trainers make sure that you are clear with all the concepts. And when you complete your course, you will also get assistance in resume preparation, etc., which gives you the confidence to clear your interview. Moreover, We are also tied up with some corporate companies. So when they have a requirement, we forward your profiles to them.

FAQ's

Yes, You need to have some coding skills. However you don't need to be perfect or an expert in coding to learn Data Science.

Any individual from Science, Engineering, technology or mathematics background is eligible for taking up this data Science Course.

If you are an individual having knowledge on core elements of data science like computer science, mathematics and statistics, you don’t feel any difficulty in learning Data Science. 

Data Scientists need a programming language to interact with the computer. There are a number of programming languages that are used by data scientists for various purposes. They are Python, SQL, R, Java, JavaScript, C/C++, Scala, etc.

Data related job roles like data scientists, data analytics, data managers, big data engineers and managers have a huge scope in the current market and will continue its demand even in the future.

Every class is recorded. If you have missed your class, you can learn those concepts from the recorded sessions of the missed class. So, No worries! 

Yes! Right from the first day of your Data Science training, our trainers make sure that you understand all the concepts and provide you with complete guidance to reach your dream job. And when you complete your course, we will also assist you in your resume preparation which will give you the confidence to clear your interview. Moreover, We are also tied up with some corporate companies. So when they have a requirement, we forward your profiles to them.

At HKR, we provide a free demo session for training seekers so they can check our quality and method of education before they enroll.

You can contact our customer care number if your query does not belong to any of the questions we have addressed in this article. We will get back to you as soon as possible.

HKR Trainings assures that the learners get a quality course from our trainers. You (the learners) will have lifetime access to recorded sessions. So in case of any doubts, you can watch these recorded sessions or even can ask your trainers to clarify them. Moreover, you will also be working on a real-time project which will help you understand the concepts more clearly. So there is no question of not being satisfied.

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