Analytics Expert Program



Duration: 100 Hours

Price: CAD 2,000

Batch Time
Saturday & Sunday 9:00 to 18:00 (EDT)

Program Overview

Supercharge your career progression by learning to make decisions that are scientific and data-driven. The Analytics Expert Program is a unique high ROI program that integrates all facets of an analytics career; Math & Stat, Programming, Data Wrangling, Visualization, Predictive Modeling, Machine Learning and Analytics Consulting within just 8 weeks of active learning. The program has cases from multiple business areas like Finance, Sales & Marketing, and HR and provides expert exposure to tools like R, Python, Power BI, Tableau, Excel and Spark. The program is led by an expert mentor and can be attended either in-class or live online. Register before Aug 26th 2018, and get FREE additional inputs to clear two major international certifications in analytics.

Course Coverage

  • Essential Mathematics and Statistics – Ace our proprietary learning techniques (TiA) to understand how to find hidden patterns in data. The approach is scalable and highly recommended for professionals interested in analytics consulting.
  • Business Intelligence – Master the art of data preparation, visualization and initial insights generation using tools like Tableau, Power BI and Excel
  • Just Enough Programming – Become proficient in R and Python and learn to perform routine and niche data analysis tasks like a Pro.
  • Predictive Modeling – Understand our proprietary model mechanics approach and gain the power to build robust models. You will learn to evaluate the models, improve their performance and communicate the results effectively.
  • Machine Learning – Implement ML algorithms that are Bias-Variance optimized. Learn to decide on critical business questions like Accuracy Vs Interpretability
  • Big Data Analytics – Learn to build analytics solutions at Scale. Understand the Big Data Ecosystem and write algorithms using Hive & PySpark.
  • Analytics Consulting – Learn to integrate your technical skills with analytics consulting by understanding how to link model performance to business profits.

Trainer Profile

Srikanth Balasubramanian has about 14 years of experience in training, consulting and software. He is a corporate trainer and an analytics consultant for Fortune 500 and MNC firms like VISA, Credit Suisse, Cisco, Honeywell, NXP, Metro, KPMG, PWC Analytics Advisory, Skoruz & Brillio technologies. He also has an extensive Machine Learning and Data Analytics consulting experience with SME firms like Merit Group and RVS Group, where he helped them set up new lines of business based on analytics despite constrained budgets and resources. He has a strong understanding of issues in analytics in the retail, marketing, and finance areas and has end-to-end capabilities to link analytical models to business goals and outcomes. He works closely with mid-career and senior folks in MNCs around the globe; USA, Singapore, Hong Kong, and India.

Program Details

  • Weekend Sessions (In-class or Live Online)
  • Saturdays and Sundays 9 am to 6 pm (Eastern Time) for 6 weekends (2 months)
  • Introductory Fee : CAD 2000 plus any applicable taxes
  • The course begins on : Sep 15, 2018
  • Venue: SDL,5200 Dixie Rd #114, Mississauga, ON L4W 1E3

Early Registrants Offer

  • One Free Attempt for Wiley Certified Big Data Analyst (WCBDA)
  • Additional 10 hrs of training focused on WCBDA International Certification ( Live online only )
  • Additional 10 hrs of training focused on Tableau Qualified Associate International Certification (Live online only)
  • Register and pay the entire fee online at www.bestintownanalytics.ca on or before Aug 26th 2018 to avail the early registration benefits.
  • Unlimited course access (Live online sessions) for a lifetime.

Refund Policy

  • 100 % Refunds less $25 administration charges for cancellations up to the end of the first day of training
  • No refunds after completing the first day of training (8 hours)
  • Program Goals : Provide a strong statistical thinking with a good understanding of the applications of probability, calculus and linear algebra in model building. Build a strong reasoning framework to convert any business problem into an inferential analytics framework.
    • Thinking in Analytics
    • Probability
    • Descriptive Statistics
    • Correlation Vs Regression
    • Central Limit Theorem
    • Hypothesis Testing
    • T-Test, Chi-Square Test and F-Test
    • ANOVA
    • Introduction to Calculus
    • Introduction to Linear Algebra
  • Program Goals : Provide a solid foundation in programming concepts required for a successful data analyst and data scientist. We learn to use R to perform data analysis and visualization. Additionally we inculcate skills to investigate data issues interactively using R Studio.
    • Data Types and Data Structures
    • Loops, Functions and Programming Elements
    • Basics of Object Oriented Programming
    • Apply family
    • Reshape2 and tidyr
    • Dplyr, ggplot2
    • Handling strings
    • Handling time series data
    • Bigmemory and iotools
    • Building dashboards in R using Rshiny
  • Program Goals : Provide a solid foundation in programming concepts required for a successful data analyst and data scientist. We learn to use Python to perform data analysis and visualization. Additionally we inculcate skills to investigate data issues interactively using Spyder.
    • Data Types and Data Structures
    • Loops, Functions and Programming Elements
    • Basics of Object Oriented Programming
    • Numpy
    • Pandas
    • Matplotlib
    • Seaborn
    • Handling time series data
    • Handling strings
    • Building Python dashboards using plotly
  • Program Goals : Convert raw data into insights and help understand what factors drive a specific business outcome and to what extent. We help in building strategies to link these models to business actions.
    • Simple Linear Regression (Marketing)
    • Multiple Regression (Marketing)
    • Logistic Regression (Finance)
    • KNN and Naïve Bayes (HR)
    • Decision Trees (Finance)
    • Bagging, Boosting & Random Forests (Finance)
    • Lasso and Ridge Regression (Finance)
    • Clustering (Marketing)
    • PCA (Marketing)
    • Neural Networks (Stock Market)
    • Support Vector Machines (Stock Market)
    • Introduction to Time Series Analysis (Finance)
    • Time Series Forecasting (Marketing)
    • Natural Language Processing (Marketing)
    • Sentiment Analysis (HR)
  • Program GoalsTo get a robust understanding of Data Science, knowledge of few other topics is very crucial. We will mainly focus on some of the other important topics needed for a Data Science professional in this section
    • Overview of SQL
    • Introduction to Tableau
    • Building dashboards in Tableau
    • Introduction to Power BI
    • Data Preparation in Power BI
    • Building dashboards in Power BI
    • Introduction to Deep Learning and AI
    • AI Applications in business
    • Introduction to Big Data and its Ecosystem
    • Introduction to Big Data Analytics
*Conditions Apply
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