Data Analytics Expert Program

What is Data Analytics?

Data analytics is a process of inspecting, cleansing, transforming, and modelling data with the goal of converting data to insights and insights to decisions in a timely and cost effective manner.

Professionals from all backgrounds; technical and managerial, require data handling and insights generation skills to be successful in this modern era where firms are competing on data not just for growth but also for survival. Data Analytics is a multi-faceted career opportunity and professionals aspiring for a career in Data Science must show interest and aptitude in Statistics, Programming, Data Visualization, Machine Learning and Big Data.

About the course

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.

Course Objectives

  • Learn to solve day-to-day business problems from a data centric approach
  • Understand what are the key factors that drive your business goals and outcomes
  • Discover the patterns in the data using explorative as well as predictive approaches
  • Become proficient in Data Visualization using tools like Tableau, Power BI and Excel
  • Understand how to build predictive models and use ML algorithms
  • Have an overview of Big Data and its ecosystem

What You’ll Learn

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.

Advanced Machine Learning:  Implement ML algorithms that are Bias-Variance optimized. Learn to decide on critical business questions like Accuracy v/s 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.

 Who Will Benefit

This program is exclusively designed to provide all the necessary skills required for anyone to start their career in Data Analytics. The program benefits can be harnessed by Students, Aspiring Data Analysts, BI Analysts and anyone who is passionate about Data and Data Analytics. The program will also be highly relevant to business professionals in Sales, Marketing, Finance and HR.

 Course Content (Module-wise)

MODULE 1: ESSENTIAL MATH & STATS FOR ANALYTICS

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.

Topics:

  • 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

MODULE 2: R FOR DATA SCIENCE

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.

Topics:

  • 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

MODULE 3: PYTHON FOR DATA SCIENCE

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.

Topics:

  • 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

MODULE 4: MACHINE LEARNING – ALGORITHMS AND IMPLEMENTATION

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.

Topics:

  • 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)

MODULE 5: OTHER ASPECTS OF DATA SCIENCE

Program Goals: To get a robust understanding of Data Science, knowledge of a 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

Topics:

  • 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 

Course Materials

  • Class Notes
  • Program codes
  • Case Study Excel sheets
  • Other learning resources 

Extra Course Benefits

  • USD 250 worth additional 10 hours of training focused on Tableau Qualified Associate International Certification (Live online only) . Please note that Exam Fee is Payable to Tableau  
  • USD 250 worth additional 10 hours of training for Wiley Certified Big Data Analyst along with PPTs to aid exam preparation. Offer also includes one free attempt of the international certification exam
  • Unlimited course access (Live online sessions) for a lifetime.

System Requirements

  • > 4 GB RAM , > 80 GB hard disk  
  • Excel 2013 or 2016 or office 365 with Solver and Data Analysis toolpak
  • We may need to install open source tools like R, RStudio, Anaconda, Tableau public