Quest Learning

by IIM Lucknow Alumna

It's been said that Data Scientist is the most sought after job title of the 21st century. Why is it such a demanded position these days? The short answer is that over the last decade there's been a massive explosion in both the data generated and retained by companies, as well as you and me. Sometimes we call this "big data," and like a pile of lumber we'd like to build something with it. Data scientists are the people who make sense out of all this data and figure out just what can be done with it.

A data scientist is the adult version of the kid who can't stop asking "Why?". They're the kind of person who goes into an ice cream shop and gets five different scoops on their cone because they really need to know what each one tastes like. Similarly, even the term data scientist is a catchall title that encompasses many different flavors of work.


Data Science course is the most popular courses and therefore no wonder that many teaching institutes have mushroomed all over the country. But most of these institutes just teaches the basics but charges a bomb from the participants.

We offer training to make you learn data science is real terms. We understand there is a major differentiator between a data scientist and a statistician or an analyst or an engineer. Data Science course is taught by industry experts who have written books on these topics and are respected in the industry. They are regarded as the experts in their field.

Some of the advanced concepts will be taught by an IIT Professor <--

    Main Content:

  • Module 1: Programming concepts in R or Python as desired by the candidate
  • Module 2: Data Visualization using R or Python
  • Module 3: Basic to Advanced Statistics concepts -using R/Python
  • Module 4: Advanced Data Analytics concepts using R or Python
  • Module 5: Machine Learning
  • Module 6: Linear Problems (Optimization)
  • Project Guidance

Detailed Structure: Module 1: Programming concepts in R or Python as desired by the candidate

  • R Overview and setup
  • Syntax
  • Data types - vector, lists, metrices, arrays, factors, data frames
  • R Variables
  • R Operators - arithmetic, relational, logical, assignment and miscellaneous
  • Decision making & loops
  • Functions in R
  • Reading from files (CSV, Excel)
  • Working with databases
  • Data Visualization
    • Overview of R Packages used for Visualization
    • Basic and Advanced Plots. GGPLOT Interactive Plots: Multiple Graphs, Title, Axes, Labels, Color Palletes, vcd, Tableplot, Googlecharts, Shiny, Rcharts, D3.js
    Module 2: Data Visualization using R or Python
    • Overview of R Packages used for Visualization
    • Basic and Advanced Plots. GGPLOT Interactive Plots: Multiple Graphs, Title, Axes, Labels, Color Palletes
    • Practice: Top 50 charts for work
    Module 3: Basic to Advanced Statistics concepts -using R/Python
    • Measure of Central Tendencies & Measure of dispersion
    • Trend lines and Trend Pattern Discussion
    • Outlier and Missing Value Treatment Analysis
    • Central Limit Theorem
    • Probability Terminology and Notations
    • Bayes Theorem & Error Matrix
    • Discrete and Continuous distributions
    • Theory of Hypothesis Testing
    • ANOVA ( One way and Two Way )
    • Explanation on F test and Z tests in summary outputs
    • Bivariate and Multivariate Analysis
    • Correlation (Positive Correlation, Negative Correlation and Types of Correlation)
    Module 4: Advanced Data Analytics concepts using R or Python
    • Tools and Techniques in Data Science
    • Getting to know your data, data cleansing and data transformation using R
    • Standard linear regression using R
    • Logistic regression using R
    • Clustering using R
    • Time series analysis
    • Market basket analysis using R
    • Text Mining
  • Module 5: Machine Learning
    • Artificial Neural Network
    • Deep Learning
    • Support Vector Machines and Kernel Regression
    • Hidden Markov Models
    • Decision Trees
    • Ensemble Methods: Random Forest, Boosting: Gradient/XG, Ada, Bagging
    • Regularization model
    • Feature selection
    Module 6: Linear Problems (Optimization)
    • Transportation, LP, Assignment Problems

    Benefits:

    • Experienced professionals from IIMs
    • Personalized training programs
    • Project work covered
    • Assignments to practice

    Call us for Demo today at: 70329 75766