Data Scientist Course in Toronto, Canada

IBM is the second-largest Predictive Analytics and Machine Learning solutions provider globally (source: The Forrester Wave report, September 2018). A joint partnership with Simplilearn and IBM introduces students to integrated blended learning, making them experts in Artificial Intelligence and Data Science. The Data Science course in Toronto offered by Simplilearn and (in collaboration with) IBM is offer to make its students job-ready for AI and Data science careers.

According to the September 2018, Forrester Wave report, IBM is the world’s second-biggest provider of Predictive Analytics and Machine Learning solutions. Simplilearn, working in partnership with IBM, introduces new students to the idea of integrated blended learning, imparting valuable expertise in Artificial Intelligence and Data Science. The Data Science course in Toronto, run in collaboration with IBM, prepares students for rewarding careers in the cutting-edge Artificial Intelligence and Data Science industries.

IBM is headquartered in Armonk, New York, and is a respected premier cognitive solutions and cloud platform company, offering a vast selection of technology and consulting services. The company is a known leader in research and development and invests $6 billion annually in these endeavors. IBM has won five Nobel prizes, five US National Medals of Science, six Turing Awards, nine US National Medals of Technology, and 10 inductions into the US Inventors Hall of Fame.

What benefits will this Data Science course in Toronto developed in collaboration with IBM give me?

After you finish the Data Scientist online Master's program, you will be awarded completion certificates from IBM and from Simplilearn for their respective courses. These data science course certificates that you'd unlock by completing the Data Science Certificate course in our Master’s program, show future employers your capability as an expert in Data Science and also prove that you've finished the Data Science training in Toronto well. You also acquire:

• 24/7 access to IBM’s cloud platforms, featuring IBM Watson and other applications so that you can sharpen your skills with practice
• Simplilearn’s industry-recognized and respected Data Scientist Master's certificate
   

Data Scientist is currently one of the most popular IT-related professions. IBM predicts Data Scientist demand will rise by 28% through 2020. This Simplilearn-IBM (in collaboration with) Data Science course Toronto offers the ideal skill set comprising data mining and visualization, clustering, wrangling, regression models, decision trees, statistics, linear and logistic regression, and hypothesis testing. You will also learn about Hadoop, PROC SQL, SAS Macros, Spark, recommendation engine, supervised and unsupervised learning, and many more valuable skills.

The Data Scientist training in Toronto, co-developed with IBM, focuses extensively in the field, bringing together online instructor-led classes and casual self-paced learning. The program ends with a world-class capstone project offered to further reinforce your the skills learned by allowing you to experience a real-industry problems that perfectly requires all the knowledge you've gained in our program. These same skills will better equip you in becoming a Data Scientist

• Gain a deep, working understanding of data structure and manipulation
• Learn about linear and non-linear regression models and classification techniques, and how to use them. This information is key to data analysis
• Acquire work-ready skils in supervised and unsupervised learning models - linear regression, K-NN, pipeline, dimensionality reduction, logistic regression and clustering.
• Conduct technical and scientific computing using the SciPy package and its sub-packages like Integrate, IO, Optimize, Statistics, and Weave, for instance.
• Obtain expertise in mathematical computing using the NumPy and Scikit-Learn packages
• Get familiarized with the various components of the Hadoop ecosystem
• Earn experience working with HBase, including its architecture, and data storage capabilities. You will also learn how to distinguish between HBase and RDBMS, and perform partitioning using Hive and Impala
• You will gain an understanding of MapReduce plus all its characteristics, as well as learning how to ingest data using key tools like Sqoop and Flume
• Master the concepts that make a recommendation engine work, and discover how to perform time series modeling. Also get a real-world exposure to ML principles, algorithms and practical applications.
• You will learn how to analyze data using Tableau, and become an expert in building interactive dashboards in this Data Science training in Toronto.

This Data Science training in Toronto features more than 15 real-life, industry-based projects highlighting different domains. These projects help you master concepts of Data Science and Big Data. Here are a few of the projects:

Capstone Project:

Description: You’ll go through dedicated mentor classes to generate a high-quality industry project where you solve a real-world problem by leveraging the skills and technologies that you learned throughout the program. The capstone project includes all the key points of data extraction, cleaning, and visualization, and how to build and tune models. You can also choose the domain/industry dataset you want to work on, based on whatever options are available.

After you successfully submit your project, you will earn a capstone certificate, showcasing your expanded learning and skills to potential employers.

Project 1: Products rating prediction for Amazon

Domain: E-commerce

Amazon, one of the leading US-based e-commerce companies, usually recommends products to customers that fall in a similar category that jibes with their activity and reviews. Amazon would like to boost this recommendation engine by increasing its capabilities, letting it predict ratings for non-rated products and adding them accordingly to the customer’s recommendations.

Project 2: Improving customer experience for Comcast

Domain: Telecom

Description: Comcast, one of the top US-based global telecommunication companies, wants to improve their customer service experience by spotting problem areas that decrease customer satisfaction, and come up with a plan on how to address these issues. The company is also looking for key recommendations that they can put in place to provide the best customer experience.

Project 3: Attrition Analysis for IBM

Domain: Workforce Analytics

Description: IBM, one of the oldest and most popular US-based IT companies, wants you to pinpoint the factors that affect employee attrition. Based on the parameters identified, the company also would like to build a logistics regression model that forecasts employee churn rate.

Project 4: Predict accurate sales for 45 Walmart stores, taking the impact of promotional markdown events into consideration. Walmart is one of America’s leading retail stores. Determine if macroeconomic factors like the Consumer Price Index, unemployment rate, etc., impact their sales.

Domain: Retail

Description: Walmart holds several promotional markdown events throughout the year. These markdowns typically precede popular holidays and annual events like the Super Bowl, Labor Day, Thanksgiving, and, naturally, Christmas. The weeks where these holidays occur have a weighing factor five times higher in valuation than regular weeks. The company, however, is facing a challenge due to unanticipated demand, a situation made worse by incorrect demand estimation. This results in occasional stock shortfalls. Macroeconomic factors such as CPI, Unemployment Index, etc. can potentially play an important role in predicting demand. However, the company hasn’t yet managed to leverage these factors. A portion of this project involves creating a model to call out the effects of these promotional markdowns on holiday weeks.

Project 5: Learn how the top healthcare industry leaders make use of Data Science to improve their business.

Domain: HealthCare

Description: Predictive analytics is a useful tool in many different aspects of healthcare, like mediating hospital readmissions. But no matter what the industry, predictors are most valuable when they’re actionable. Or, put another way, historical and real-time data alone are useless unless the company makes a move. More importantly, in order to ascertain the value and effectiveness of forecasting a trend and ultimately changing the behavior, you must be able to incorporate both the predictor and the intervention back into the same workflow and system where the trend originally started.

Project 6: Understand how Insurance leaders like AIG, AXA, Berkshire Hathaway, etc., use Data Science by working on an insurance-based real-life project in this data science course in Toronto

Domain: Insurance

Description: According to information in the 2013 Insurance Predictive Modeling Survey, predictive analytics has risen sharply in the insurance industry, particularly in the biggest companies. For example, the survey shows a predictive modeling boost across the industry, but there are disparities. In fact, every insurance company that writes more than $1 billion in personal insurance uses predictive modeling, while companies who deal with less than that amount hover in the 69% utilization range.

Project 7: See how large banks like Bank of America, Citigroup, ICICI, HDFC, etc. use Data Science to stay ahead of the competition.

Domain: Banking

Description: A Portuguese banking institution held a marketing campaign to give prospective customers a good reason to invest in a bank term deposit. The bank used phone calls to conduct their marketing campaigns. However, sometimes the same customer got repeated calls, resulting in duplication of effort. Your job is to analyze all the data gathered from this banking marketing campaign.

Project 8: Learn how stock markets like NASDAQ, NSE, and BSE leverage Data Science and Analytics to derive consumable data from complex data sets in this data science training in Toronto.

Domain: Stock Market

Description: You must import data from the following companies, using the Yahoo data reader: Amazon, Apple, Google, Microsoft, x and Yahoo. Using the data available, you'll do fundamental analytical functions - (daily) return analysis, closing price plots, stock trade volume plots and correlation plots (using pair plots) between multiple stocks.

Project 9: Understand how Data Science is used in the field of engineering by engaging in this case study of MovieLens Dataset Analysis.

Domain: Engineering

Description: The GroupLens Research Project is a research group based at the University of Minnesota’s Department of Computer Science and Engineering. The researchers there are involved in several projects related to collaborative filtering, information filtering, and recommender systems.

Project 10: See how top retail companies like Amazon, Walmart, Target, etc. utilize Data Science to analyze and optimize their product placements and stock inventory.

Domain: Retail

Description: Companies use Analytics to optimize product shelf placement in their stores or the inventory in their warehouses. With this project, participants learn about the daily cycle of product optimization from the warehouse to the shelves. This gives the company insights into regular occurrences in the retail sector.

The most effective Data Scientists possess a combination of experience, data science knowledge, and the appropriate tools and technologies. It’s a great career choice, perfect for both rookies and seasoned professionals alike. Data Science aspirants who have an analytical mindset and an education in a related preliminary field will find this Data Science training in Toronto to the ideal boost for positions like:

• 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

If any professional is seeking to enroll and extract maximum impact out of this Simplilearn offered Data Scientist Course in Toronto, what they’d need would be:

• Fundamental know-how of Statistics
• A good foundational-level programming language understanding

On becoming a program graduate of our Data Science course in Toronto, you'd have acquired an in-demand skills set in the field of data science, which you can then use to compete for today's top roles, including:

• Data Scientist 
• Data Analytics Expert
• Lead/Manager - Analytics 
• Machine Learning(ML) Engineer
• Specialist - Statistical Programming

Data extends into all areas of our lives, and Data Scientists are, unsurprisingly, the top-ranking professionals in any analytics organization. The Glassdoor employment site ranks the Data Scientist profession second in the 50 Best Jobs for 2021. There’s a shortage of Data Scientists, making them much in demand in today’s job market. Data Scientists today are primarily required to have a shard understanding of the real-world business issues, perform data gathering and cleaning, device accurate strategies (data analytical), implement the right algorithms/techniques (by utilizing appropriate tools) and consequently making data-driven, actionable steps forward. That’s why it’s wise to take a data science course in Toronto.