Learn from Home Offer
Data Scientist Course in Canada (85 Courses, 67+ Projects)
85 Online Courses
67 Hands-on Projects
660+ Hours
Verifiable Certificate of Completion
Lifetime Access
Python Data Scientist Courses (18 Courses)
Python Data Scientist Projects (6 Projects)
R Programming Data Scientist Courses (12 Courses)
R Programming Data Scientist Projects (11 Projects)
SAS Data Scientist Courses (9 Courses)
* One Time Payment & Get Lifetime Access
What you get in this Data Scientist Course in Canada?
Online Classes
Technical Support
Mobile App Access
Case Studies
About Data Scientist Course Canada
Course | No. of Hours | |
---|---|---|
Machine Learning with Python 2022 | 5h 15m | |
Project on Machine Learning - Covid19 Mask Detector | 2h 05m | |
Machine Learning Project - Auto Image Captioning for Social Media | 2h 23m | |
Machine Learning with SciKit-Learn in Python | 8h 37m | |
Machine Learning Python Case Study - Predictive Modeling | 8h 27m | |
Matplotlib for Python Developers - Beginners | 4h 12m | |
Matplotlib for Python Developers - Intermediate | 2h 52m | |
Matplotlib for Python Developers - Advanced | 6h 37m | |
Pandas with Python Tutorial | 5h 47m | |
NumPy and Pandas Python | 5h 01m | |
Pandas Python Case Study - Data Management for Retail Dataset | 3h 28m | |
Python Case Study - Sentiment Analysis | 1h 06m | |
Data Science with Python | 4h 14m | |
Artificial Intelligence with Python - Beginner Level | 2h 49m | |
Artificial Intelligence with Python - Intermediate Level | 4h 36m | |
AI Artificial Intelligence with Python | 6h 15m | |
Video Analytics using OpenCV and Python Shells | 2h 13m | |
Machine Learning using Python | 3h 26m | |
Statistics Essentials with Python | 3h 23m | |
Project on Tensorflow - Implementing Linear Model with Python | 1h 46m | |
Project - Data Analytics with Data Exploration Case Study | 5h 7m | |
Project on ML - Random Forest Algorithm | 1h 29m | |
Seaborn Python - Beginners | 2h 28m | |
Seaborn Python - Intermediate | 1h 18m | |
Seaborn Python - Advanced | 1h 56m | |
PySpark Python - Beginners | 2h 3m | |
PySpark Python - Intermediate | 2h 05m | |
PySpark Python - Advanced | 1h 14m | |
Machine Learning Python Case Study - Diabetes Prediction | 1h 03m | |
R Studio UI and R Script Basics | 4h 9m | |
R Programming for Data Science | A Complete Courses to Learn | 5h 7m | |
R Practical - Logistic Regression with R | 4h 18m | |
Project - Decision Tree Modeling using R | 1h 44m | |
Project on ML - Churn Prediction Model using R Studio | 1h 22m | |
Financial Analytics in R - Beginners | 3h 5m | |
Financial Analytics in R - Intermediate | 1h 28m | |
Financial Analytics in R - Advanced | 1h 35m | |
R for Finance - Beginners to Beyond | 2h 17m | |
Comprehensive Course on R | 3h 54m | |
Project on R - Forecasting using R | 4h 34m | |
Project - Fraud Analytics using R & Microsoft Excel | 2h 34m | |
Project - Marketing Analytics using R and Microsoft Excel | 2h 9m | |
Machine Learning with R | 20h 28m | |
Case Study - Customer Analytics using Tableau and R | 2h 7m | |
Case Study - Pricing Analytics using Tableau and R | 2h 39m | |
Business Analytics using R - Hands-on! | 16h 21m | |
Project - Market Basket Analysis in R | 37m | |
Project - Hypothesis Testing using R | 3h 6m | |
Data Visualization with R Shiny - The Fundamentals | 39m | |
Data Science with R | 6h 2m | |
R Studio Anova Techniques Course | 2h 18m | |
SAS Business Analytics for Beginners | 10h 42m | |
Predictive Modeling with SAS Enterprise Miner | 9h 21m | |
Quantitative Finance with SAS | 3h 29m | |
SAS Statistics | 8h 18m | |
SAS ODS (Output Delivery System) | 9h 08m | |
SAS PROC SQL | 13h 49m | |
SAS Macros | 7h 38m | |
SAS Advanced Analytics | 12h 34m | |
SAS Graph | 2h 1m | |
SAS DS2 | 5h 2m | |
SAS SQL | 3h 03m | |
SAS Practical - Macros | 5h 12m | |
SAS Advanced Programming | 11h 24m | |
SAS Categorical Data Analysis | 7h 26m | |
Certified SAS Base Programmer | 12h 2m | |
SAS Features for Starters | 1h 5m | |
SAS PROC SQL Features | 1h 53m | |
Big Data and Hadoop Training | Online Hadoop Course | 2h 3m | |
Hadoop Architecture and HDFS | 6h 13m | |
MapReduce - Beginners | 3h 34m | |
MapReduce - Advanced | 5h 35m | |
Hive - Beginners | 2h 47m | |
Hive - Advanced | 5h 11m | |
PIG - Beginners | 2h 1m | |
PIG - Advanced | 2h 13m | |
NoSQL Fundamentals | 2h 01m | |
Mahout | 3h 51m | |
Apache Oozie | 2h 13m | |
Apache Storm | 2h 4m | |
Apache Spark - Beginners | 1h 5m | |
Apache Spark - Advanced | 6h 14m | |
Splunk Fundamentals | 8h 33m | |
Splunk Advanced 01 - Knowledge Objects | 9h 29m | |
Splunk Advanced 02 - Administration | 39h | |
Project on Hadoop - Sales Data Analysis | 47m | |
Project on Hadoop - Tourism Survey Analysis | 53m | |
Project on Hadoop - Faculty Data Management | 35m | |
Project on Hadoop - E-Commerce Sales Analysis | 35m | |
Project on Hadoop - Salary Analysis | 49m | |
Project on Hadoop - Health Survey Analysis using HDFS | 56m | |
Project on Hadoop - Traffic Violation Analysis | 1h 25m | |
Project on Hadoop - Analyze Loan Dataset using PIG/MapReduce | 2h 33m | |
Project on Hadoop - Case Study on Telecom Industry using HIVE | 2h 2m | |
Project on Hadoop - Customers Complaints Analysis using HIVE/MapReduce | 53m | |
Project on Hadoop - Social Media Analysis using HIVE/PIG/MapReduce/Sqoop | 3h 34m | |
Project on Hadoop - Sensor Data Analysis using HIVE/PIG | 5h 26m | |
Project on Hadoop - Youtube Data Analysis using PIG/MapReduce | 3h 02m | |
Hadoop and HDFS Fundamentals on Cloudera | 1h 22m | |
Project on Hadoop - Log Data Analysis | 1h 32m | |
SPSS 2022 - Beginners | 1h 05m | |
SPSS 2022 - Advanced | 5h 22m | |
Advanced SPSS Project: Impact of EMI on Home Loan | 43m | |
Advanced SPSS Project: Impact of Total Turnover in Equity Market | 58m | |
Advanced SPSS Project: Impact of Trade Data in Equity Market | 46m | |
SPSS GUI and Applications | 1h 13m | |
SPSS - Correlation Techniques | 1h 8m | |
SPSS - Linear Regression Modeling | 3h 08m | |
SPSS - Multiple Regression Modeling | 2h 34m | |
SPSS - Logistic Regression | 2h 01m | |
SPSS - Multinomial Regression | 2h 2m | |
SPSS GUI for Statistical Analysis | 2h | |
Tableau Desktop Training 2022 | 4h 17m | |
Tableau Project-Creating Dashboard and Stories For Financial Markets | 2h 08m | |
Tableau Project - Russo-Ukraine War A Data Analytical Review | 1h 02m | |
Tableau | 4h 7m | |
BI Tools and Tableau Analytics | 5h 38m | |
Business Intelligence with Tableau | 5h 43m | |
Tableau Features Hands-on! | 5h 32m | |
Tableau Practical - Super Store Business Requirements | 45m | |
Analytics using Tableau | 9h 29m | |
Minitab for Beginners - 2022 | 1h 12m | |
Advanced Minitab Training - 2022 | 4h 39m | |
Minitab Practical - Impact of Predictors on Response | 1h 36m | |
Statistical Analysis using Minitab - Beginners to Beyond | 4h 27m | |
Minitab GUI and Descriptive Statistics | 2h 43m | |
ANOVA in Minitab | 53m | |
Correlation Techniques in Minitab | 2h 21m | |
Project on Minitab - Regression Modeling | 9h 54m | |
Minitab Predictive Modeling using Excel | 55m | |
MATLAB - Beginners | 2h 58m | |
MATLAB - Intermediate | 47m | |
MATLAB - Advanced | 4h 1m | |
Oracle SQL | 17h 32m | |
Oracle PLSQL | 13h 2m | |
Oracle DATABASE Admin DBA 1 Course | 9h 27m | |
Machine Learning with Tensorflow | 13h 29m | |
Hands-on Deep Learning Training | 10h 8m | |
Project - Exploratory Data Analysis EDA using ggplot2, R and Linear Regression | 2h 07m | |
Project on R - HR Attrition and Analytics | 2h 43m | |
Logistic Regression using SAS Stat | 4h 28m | |
Linear Regression in Python | 2h 28m | |
Python Data Science Case Study - Predicting Survival of Titanic Passengers | 2h 6m | |
Project on R - Card Purchase Prediction | 2h 28m | |
Machine Learning Python Case Study - Develop Movie Recommendation Engine | 51m | |
R Practical - Employee Attrition Prediction using Random Forest Technique and R | 1h 6m | |
Project on Term Deposit Prediction using Logistic Regression CART Algorithm | 1h 38m | |
Poisson Regression with SAS Stat | 2h 22m | |
Machine Learning Project using Caret in R | 1h 58m | |
Time Series Analysis in Python - Sales Forecasting | 2h 12m |
Course Name | Online Data Scientist Course Canada |
Deal | You get access to all videos for the lifetime |
Hours | 660+ Video Hours |
Core Coverage | You get to learn data science using R, Python, Machine Learning, Artificial Intelligence, Big data & Hadoop, Predictive Modeling, Business Analytics, Data Visualization, and other areas under Data Science. |
Course Validity | Lifetime Access |
Eligibility | Anyone serious about learning data science and wants to make a career in analytics |
Pre-Requisites | Basic knowledge of data and analytics |
What do you get? | Certificate of Completion for the course |
Certification Type | Course Completion Certificates |
Verifiable Certificates? | Yes, you get verifiable certificates for each85 course, 67 Projects with a unique link. These link can be included in your resume/Linkedin profile to showcase your enhanced skills |
Type of Training | Video Course – Self Paced Learning |
Software Required | None |
System Requirement | 1 GB RAM or higher |
Other Requirement | Speaker / Headphone |
Data Scientist Course in Canada Curriculum
This training program has been very carefully designed and developed to fulfill the requirements of everyone willing to learn Data Science, people regardless of their knowledge of any data science element. Python derived units are the main part of the course. You learn how python is used in these units to work with large quantities of data to produce useful information. You can learn about Python’s special libraries with numerous features and the user can extend the features in the application. You will also learn about R programming, another important part of data science. Many program features are implemented using the language of R programming and you will learn them in this Data Scientist Course in Canada. However, via SAS you will also learn about data science and take part in the live campaign. The learning and the project part are available for all subjects included in this course. The project helps you to understand the internal workings of the system through the technologies or techniques described above.
The course provides you with a deep knowledge of modules such as SPSS, Minitab, Hadoop, Tableau. The approach, which is considered as data science, is endorsed by every topic defined here. Finally, before you finish your course you will be able to get to know Matlab and Splunk so that you can learn all aspects of data science. Along with the topics, projects are being developed for each technology or tool that has been introduced in this Data Scientist Course in Canada to help you get hands-on experience. During the time you practice your task, you will learn about the real-time problems in the production environment and overcome these problems can help you to understand the technology deeply.
Data Scientist Course – Certificate of Completion
Who is a Data Scientist?
The data scientist can be described as an expert with huge amounts of data to extract useful information from it. A data scientist uses many information-processing techniques. We generally use languages such as python and R that have a good understanding of different frameworks. A data scientist’s core role is to process the data through the application of algorithms and unique methods. He also understands technologies such as MatLab, Hadoop, Splunk, etc. The organization which handles much data is required to make the decision.
In the graphical representation, the data scientists can also produce data, making decision-making too easy. They also know how to conduct mathematical calculations based on statics that support the data processing, as well as the programming abilities and knowledge of several techniques. In reality, they transform the mathematical form into an algorithm to process the data and produce useful data.
Which Skills will you learn in this Course?
This Data Scientist Course in Canada includes all the elements you need to know to be a data scientist. Because the topics are python-based, you can learn more about python and certain frameworks. You’ll also learn the R language programming which data scientists need. You will also learn to work on other software such as Splunk, MatLab, SAS, Minitab, image, etc. The course also includes the project module introduced to give you real skills. You will all be a data scientist in all the units that are covered in this course, and these are your skills.
Pre-requisites
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- There are certain preconditions for certain courses that must be met to proceed. But in this situation, we have nothing as a requirement, but certain technologies will promote training for you.
- is the first thing. The software designed for data processing in Python is built using different frameworks. If you know how to code Python and R you will be very helpful. Apart from that, some of the tools or technologies can help you to be a data scientist. A basic understanding of technologies such as Hadoop, Minitab, MatLab, and Splunk should be found.
Target Audience
- Everyone trying to learn can be the best target audience for any course and the same implies to this Data Scientist Course in Canada. The best audience for this training can be professionals interested in expanding their careers in the field of data science. Upon completing this course, you will get to learn various new things and be rewarded in the interviews or current work. The students who are ready to be a data scientist in the final year of their studies will start their career in this course. Since this Data Scientist Course in Canada focuses mainly on the practical side, the students will learn a lot of new things in their academics.
Data Scientist Course Canada – FAQ’s
Why should you study data science in Canada?
Organizations in India are exponentially expanding their eCommerce & online service.
Organizations look for candidates who have extensive experience working with the data and help them obtain accurate information. As a data scientist in India, it’s much more competitive because of the high demand for skilled data scientists. There are huge job opportunities in the current labor market and the near future, the number will grow rapidly.
You may choose to take this Data Scientist Course in Canada that will improve your data science skills if you want to use the highly demanding software.
How long is the validation period?
This Data Scientist Course in Canada credentials is valid for a lifetime. It is necessary to change all the certificates. You can also take further advanced courses to increase your understanding and help you develop your career.
How long is this Data Science Course going to take?
It is generally recommended 10 -15 hours a week. Time to complete the course may differ, but the majority of students can complete the course in 6 to 7 months if they are given 10 – 15 hours a day
Will the course obtain a certificate?
Yeah, that’s right. The Data Science course is awarded to all those students who successfully pass the course along with project completion and who earn a lifetime validity certificate.
What is the Data Science market trend in Canada?
It’s not long since strong growth has been recorded by data science. Canada is big with a population of lakhs and most of them use the internet to produce huge knowledge. Businesses in Canada required specialized and extensive technology to handle this information, and that was the time when data science made its debut in Canada. A few years ago, this technology was not so demanding, but at the same time it is highly demanded in Canada and virtually all of the industries need the expert in data science. The phenomenon is already booming and is to be intensified shortly.
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Career Benefits
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- This Data Scientist Course in Canada includes all the modules that someone prepared to develop his or her
- requires. You can learn advanced new technologies, as this course covers all the subjects that fall within the Data Science Court. The important part of this training is that you know how the project in data science is done in combination with the learning component because every system or software has a project module. You can work as a data scientist after completing this Data Scientist Course in Canada and can also manage work on your own in the manufacturing environment. You may wish to become involved in the area of data science if you are looking for a rewarding career that offers better competitions.
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Reviews
Data science with python
The course goes through the different areas of data science with python. Besides a fundamental theory regarding the explained concepts, the diverse concepts are exemplified with short python programs. The lessons are good to understand and the programs presented to illustrate and implement the concepts are simple and significant.
Linked
Jorge Giro
Business Analytics using R
The data scientist course was very comprehensive and covered in detail the business analytics using R. The tutor used clear English and explained very carefully the different topics of the course. It is very rare to find a course online that covers that much information going from the basics of statistics to the application of R to business analytics. I think this is a competitive advantage of the course since the majority of this kind of courses available online are made for people who already know statistics or even some knowledge about the software itself, but this Data scientist course tried to cover them all which made very comfortable for me as a student.
Linked
Abderrahmane Friha
Amazing First Sashay with Customer Analytics
If you’re looking to dipping your toes into customer analytics, this Data scientist course is a good first start. It provides the foundation knowledge for customer analytics from mapping out the customer lifecycle and drilling down on what needs to be down per phase of the said lifecycle. I need to note that the data scientist training course explains from a bank / financial service standpoint, though this I feel allows the course to explain the concepts better instead of not having any examples at all.
Linked
Acee Vitangcol
Great content
Amazing material put together, it goes in-depth with functions on Excel, R, and SAS. I like the complexity and the level of knowledge especially the Excel area. If you are looking to analyze data regularly using excel 2010, or similar platforms such as R, this training is full of great content at a very high level.
Linked
Jorge Dominguez
Good Introduction to Marketing Analytics
It is a good Introduction to Marketing Analytics. It lists the typical activities carried out in the practice of predictive analytics. Furthermore, it helps to define how to make analytics more efficient, lists the type of models that are used in marketing and digital marketing, and some hints on the leading vendors of predictive analytics.
Linked
Ricardo Garibay-Martínez