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Data Analytics Program

3,489 Ratings

Learn from University of Toronto Faculty and Industry Experts with Three Guaranteed Job Interviews

Master the skills of data analytics with this Data Analytics certification course. Learn from Rotman School of Management faculty and industry experts to master the skills required to become a data analyst like Statistics and data analysis. You will work on multiple real-world projects and assignments that will help you become industry-ready and a certified data analyst. Rotman School of Management faculty will teach Linear Algebra and advanced statistics.

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Learning Format

Online Bootcamp

Live Classes

7 months

3 Guaranteed

Interviews

Certifications

Rotman & Intellipaat

500+

Hiring Partners

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About the Program

Through the Rotman (University of Toronto) Data Analytics program, you will gain an in-depth understanding of SQL, Python, Excel, Power BI, data warehousing, etc. The course is split into 8 carefully designed modules by top industry experts to help you master the concepts of data analytics.

Key Highlights

50+ Live sessions for a period of 7 months
218 Hours of Self-Paced Learning
One-on-One interaction with mentors
24*7 Support
Learn from the faculty of the Rotman School of Management and Industry Experts
40+ Industry Projects and Case Studies
12 hrs sessions from Rotman Faculty
Dedicated learning management team
Career Services by Intellipaat
Soft Skills Essential Training
No-Cost EMI Option
3 Guaranteed Interviews upon clearing PRT

About Rotman School of Management (University of Toronto)

The Rotman School of Management is part of the University of Toronto, a global center of research and academic excellence. The Rotman School's history of transforming business education goes back to 1901. Over the past 15 years, the School has quadrupled its endowment and tripled its physical footprint, faculty, and its student body.

Key achievements of Rotman School of Management (University of Toronto)

  • Ranked #1 Business School in Canada by QS Global MBA Rankings, 2023
  • It is ranked #13 in the World University Rankings
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Note: All certificate images are for illustrative purposes only and may be subject to change at the discretion of the Rotman School of Management.

Career Transition

55% Average Salary Hike

$1,20,000 Highest Salary

12000+ Career Transitions

400+ Hiring Partners

Career Transition Handbook

*Past record is no guarantee of future job prospects

Who can apply for this Data Analytics program?

  • Non-IT Professionals in sectors such as HR, banking, marketing, and sales, etc.
  • BI Professionals
  • Data Analytics Professionals
  • Project Managers
  • Software Developers
  • Information Architects
  • Freshers and Undergraduates can apply for the course as well
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What roles can a Data Analyst professional play?

Data Analyst

Create predictive models like churn likelihood, customer lifetime value, and more and help the team implement these models accordingly.

Data Scientist

Develop models concerning numerous cost components that power the various margin awareness initiatives.

Data Analytics Specialist

Maintain the specifications of data engineering and meet the objectives in online data visualization platforms, such as Alteryx and Tableau.

Visualization & Reporting Analyst

Build attractive, interactive, and intuitive data visualizations, including reports, graphs, presentations, and dashboards.

Business Intelligence Analyst

Identify, build, and execute the techniques of data analysis to allow the team to make significant impacts on the business.

Business Analyst

Identify, build, and execute the techniques of data analysis to allow the team to make significant impacts on the business.

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Skills to Master

SQL

Python

Data Visualization

Power BI

Data Warehousing

Machine Learning

Excel

Advanced Statistics

Data Mining

R programming

Prediction Algorithms

Data Analysis

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Tools to master

python SQL R excel Power-BI Knime
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Meet Your Mentors

Curriculum

Live Course Self Paced Industry Expert Academic Faculty

1. SQL Basics –

  • Fundamentals of Structured Query Language
  • SQL Tables, Joins, Variables

2. Advanced SQL –

  • SQL Functions, Subqueries, Rules, Views
  • Nested Queries, string functions, pattern matching
  • Mathematical functions, Date-time functions, etc.

3. Deep Dive into User Defined Functions

  • Types of UDFs, Inline table value, multi-statement table.
  • Stored procedures, rank function, SQL ROLLUP, etc.

4. SQL Optimization and Performance

  • Record grouping, searching, sorting, etc.
  • Clustered indexes, common table expressions.
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  1. Introduction to Python and IDEs – The basics of the python programming language, how you can use various IDEs for python development like Jupyter, Pycharm, etc.
  2. Python Basics – Variables, Data Types, Loops, Conditional Statements, functions, decorators, lambda functions, etc.
  3. Object Oriented Programming – Introduction to OOPs concepts like classes, objects, inheritance, abstraction, polymorphism, encapsulation, etc.
  4. Hands-on Sessions And Assignments for Practice – The culmination of all the above concepts with real-world problem statements for better understanding.
  5. Data Handling with NumPy
    1. NumPy Arrays, CRUD Operations, etc.
    2. Linear Algebra – Matrix multiplication, CRUD operations, Inverse, Transpose, Rank, Determinant of a matrix, Scalars, Vectors, Matrices.
  6. Data Manipulation Using Pandas
    1. Loading the data, dataframes, series, CRUD operations, splitting the data, etc.
  7. Data Preprocessing
    1. Exploratory Data Analysis, Feature engineering, Feature scaling, Normalization, standardization, etc.
    2. Null Value Imputations, Outliers Analysis and Handling, VIF, Bias-variance trade-off, cross validation techniques, train-test split, etc.
  8. Data Visualization
    1. Bar charts, scatter plots, count plots, line plots, pie charts, donut charts, etc, with Python matplotlib.
    2. b. Regression plots, categorical plots, area plots, etc, with Python seaborn.
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1. Descriptive Statistics –

  • Measure of central tendency, measure of spread, five points summary, etc.

2. Probability

  • Probability Distributions, bayes theorem, central limit theorem.

3. Inferential Statistics –

  • Correlation, covariance, confidence intervals, hypothesis testing, F-test, Z-test, t-test, ANOVA, chi-square test, etc.
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1. Introduction to Machine learning

  • Supervised, Unsupervised learning.
  • Introduction to scikit-learn, Keras, etc.

2. Regression

  • Introduction classification problems, Identification of a regression problem, dependent and independent variables.
  • How to train the model in a regression problem.
  • How to evaluate the model for a regression problem.
  • How to optimize the efficiency of the regression model.
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1. Excel Fundamentals

  • Reading the Data, Referencing in formulas, Name Range, Logical Functions, Conditional Formatting, Advanced Validation, Dynamic Tables in Excel, Sorting and Filtering
  • Working with Charts in Excel, Pivot Table, Dashboards, Data and File Security
  • VBA Macros, Ranges and Worksheet in VBA
  • IF conditions, loops, Debugging, etc.

2. Excel For Data Analytics

  • Handling Text Data, Splitting, combining, data imputation on text data, Working with Dates in Excel, Data Conversion, Handling Missing Values, Data Cleaning, Working with Tables in Excel, etc.

3. Data Visualization with Excel

  • Charts, Pie charts, Scatter and bubble charts
  • Bar charts, Column charts, Line charts, Maps
  • Multiples: A set of charts with the same axes, Matrices, Cards, Tiles

4. Excel Power Tools

  • Power Pivot, Power Query and Power View

5. Classification Problems using Excel

  • Binary Classification Problems, Confusion Matrix, AUC and ROC curve
  • Multiple Classification Problems

6. Information Measure in Excel

  • Probability, Entropy, Dependence
  • Mutual Information

7. Regression Problems Using Excel

  • Standardization, Normalization, Probability Distributions
  • Inferential Statistics, Hypothesis Testing, ANOVA, Covariance, Correlation
  • Linear Regression, Logistic Regression, Error in regression, Information Gain using Regression
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1. Power BI Basics

  • Introduction to PowerBI, Use cases and BI Tools, Data Warehousing, Power BI components, Power BI Desktop, workflows and reports, Data Extraction with Power BI.
  • SaaS Connectors, Working with Azure SQL database, Python and R with Power BI
  • Power Query Editor, Advance Editor, Query Dependency Editor, Data Transformations, Shaping and Combining Data, M Query and Hierarchies in Power BI.

2. DAX

  • Data Modeling and DAX, Time Intelligence Functions, DAX Advanced Features

3. Data Visualization with Analytics

  • Slicers, filters, Drill Down Reports
  • Power BI Query, Q & A and Data Insights
  • Power BI Settings, Administration and Direct Connectivity
  • Embedded Power BI API and Power BI Mobile
  • Power BI Advance and Power BI Premium
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In this module, you will learn about all the intricacies that are involved in the implementation of large-scale data warehouses for data analytics.

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1. Introduction to Spark
2. Spark Basics
3. Working with RDDs in Spark
4. Aggregating Data with Pair RDDs
5. Writing and Deploying Spark Applications
6. Parallel Processing
7. Spark RDD Persistence
8. Spark MLlib
9. Integrating Apache Flume and Apache Kafka
10. Spark Streaming
11. Improving Spark Performance
12. Spark SQL and Data Frames
13. Scheduling/Partitioning in Spark

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  • This project focuses on establishing a strong hold of analyzing a problem and coming up with solutions based on insights from the data analysis perspective. The capstone project will help you master the following verticals:
    • Extracting, loading and transforming data into usable format to gather insights.
    • Data manipulation and handling to pre-process the data.
    • Feature engineering and scaling the data for various problem statements.
    • Model selection and model building on regression problems using supervised/unsupervised machine learning algorithms.
    • Assessment and monitoring of the model created using the machine learning models.
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Disclaimer
Intellipaat reserves the right to modify, amend or change the structure of module & the curriculum, after due consensus with the university/certification partner.

Program Highlights

50+ Live session for a period of 7 months
218 Hours of Self-Paced Learning
50+ Industry Projects & Case Studies
24*7 Support

Project Work

All the projects included in this program are aligned with the industry demands and standards. These industry-oriented projects will test your level of knowledge in the data analytics domain and also help you get exposure to real-life scenarios.

Practice 20+ Essential Tools

Designed by Industry Experts

Get Real-world Experience

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Career Services By Intellipaat

Career Services
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Career Oriented Sessions

Throughout the course

Over 20+ live interactive sessions with an industry expert to gain knowledge and experience on how to build skills that are expected by hiring managers. These will be guided sessions and that will help you stay on track with your up skilling objective.

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Resume & LinkedIn Profile Building

After 70% of course completion

Get assistance in creating a world-class resume & Linkedin Profile from our career services team and learn how to grab the attention of the hiring manager at profile shortlisting stage.

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Mock Interview Preparation

After 80% of the course completion

Students will go through a number of mock interviews conducted by technical experts who will then offer tips and constructive feedback for reference and improvement.

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1 on 1 Career Mentoring Sessions

After 90% of the course completion

Attend one-on-one sessions with career mentors on how to develop the required skills and attitude to secure a dream job based on a learners’ educational background, past experience, and future career aspirations.

guaranteed

3 Guaranteed Interviews

Upon movement to the Placement Pool

Guaranteed 3 job interviews upon movement to the placement pool after clearing the Placement Readiness Test ( PRT). Get interviewed by our 400+ hiring partners.

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Exclusive access to Intellipaat Job portal

After 80% of the course completion

Exclusive access to our dedicated job portal and apply for jobs. More than 400 hiring partners’ including top start-ups and product companies hiring our learners. Mentored support on job search and relevant jobs for your career growth.

Our Alumni Works At

Hiring-Partners

Peer Learning

Via Intellipaat PeerChat, you can interact with your peers across all classes and batches and even our alumni. Collaborate on projects, share job referrals & interview experiences, compete with the best, make new friends – the possibilities are endless and our community has something for everyone!

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Admission Details

The application process consists of three simple steps. An offer of admission will be made to selected candidates based on the feedback from the interview panel. The selected candidates will be notified over email and phone, and they can block their seats through the payment of the admission fee.

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Submit Application

Tell us a bit about yourself and why you want to join this program

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Application Review

An admission panel will shortlist candidates based on their application

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Admission

Selected candidates will be notified within 1–2 weeks

Program Fee

Total Admission Fee

$ 2,632

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Frequently Asked Questions

Is data analytics a good career option?

A career in the data analytics domain is not just a good career option but one of the most popular careers today. You can find jobs in this domain across a diverse range of industries and companies around the globe by completing this training in data analytics.

As per the Bureau of Labour Statistics, the estimated growth rate for data analytics professionals will shoot up by 23% by the year 2026.

If you are looking for free resources on data analytics then read our blogs on data analytics tutorials, data analytics interview questions, and also visit our YouTube channel for free videos.

The tools used for data analysis make the tasks of data processing, data manipulation, data analysis, and pattern and trend identification much easier. Some of the top data analysis tools are:

  • R programming
  • Tableau Public
  • QlikView
  • RapidMiner
  • KNIME
  • Excel
  • Apache Spark
  • Splunk
  • SAS

Data Analytics: Data Analytics involves the process of discovering, interpreting, visualizing, and reporting the patterns in data that can drive business strategy, decisions, and outcomes.

Data Analysis: Data Analysis is a subset of the broader field of Data Analytics. Data Analysis consists of specific actions such as data cleaning, transformation, modeling, and questioning to help find useful information from a single and already prepared set of data.

Data Analysts: Data Analysts are those professionals who come up with meaningful insights from the data. They have both the technical expertise and the communication skills to derive and present quantitative findings to technical and non-technical teams, clients, and stakeholders.

Intellipaat offers self-paced training to those who wish to learn at their own pace. This training also gives you benefits like query resolution through email, live sessions with trainers, round-the-clock support, and access to the learning modules on LMS for an entire lifetime. Also, you will get the latest version of the course material at no additional cost.

Intellipaat’s self-paced training is priced 75 percent lesser compared to online instructor-led training. If you face any problems while learning, our team can always arrange a virtual live class with the trainers as well.

At Intellipaat, you can enroll in either instructor-led online training or self-paced training. Apart from this, Intellipaat also offers corporate training for organizations to upskill their workforce. All trainers at Intellipaat have 12+ years of relevant industry experience, and they have been actively working as consultants in the same domain, which has made them subject matter experts. Go through the sample videos to check the quality of our trainers.

Intellipaat is offering you the most updated, relevant, and high-value real-world projects as part of the training program. This way, you can implement the learning that you have acquired in real-world industry setup. All training comes with multiple projects that thoroughly test your skills, learning, and practical knowledge, making you completely industry-ready.

You will work on highly exciting projects in the domains of high technology, ecommerce, marketing, sales, networking, banking, insurance, etc. After completing the projects successfully, your skills will be equal to 6 months of rigorous industry experience.

Intellipaat actively provides placement assistance to all learners who have successfully completed the training. For this, we are exclusively tied-up with over 80 top MNCs from around the world. This way, you can be placed in outstanding organizations such as Sony, Ericsson, TCS, Mu Sigma, Standard Chartered, Cognizant, and Cisco, among other equally great enterprises. We also help you with the job interview and résumé preparation as well.

Once you complete Intellipaat’s training program, working on real-world projects, quizzes, and assignments and scoring at least 60 percent marks in the qualifying exam, you will be awarded Intellipaat’s course completion certificate. This certificate is very well recognized in Intellipaat-affiliated organizations, including over 80 top MNCs from around the world and some of the Fortune 500 companies.

All the sessions at Intellipaat are recorded and will be available to the learners within 12 hours after the session. If by any circumstance, you missed the live class, you can go through the recordings. Also, if you need any support, you will have access to 24*7 technical support for any sort of query resolution.

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What is included in this course?

  • Non-biased career guidance
  • Counselling based on your skills and preference
  • No repetitive calls, only as per convenience
  • Rigorous curriculum designed by industry experts
  • Complete this program while you work