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Essential Features

Full-time Faculty

Our trainers are there to guide you on a full time basis .We do not believe in ad hoc arrangements for faculties. We believe in establishing the connect with students.

Placement Assistance

The WallStreet School provides 100% placement assistance to the delegates who have successfully completed our Big Data Analytics training programme.

Experiential learning

Our trainers are Ex-consultants and Ex-investment bankers of reputed companies sucha as Mckinsey and Goldman Sachs. They bring real business problems to the classroom.

Certification

To add-up the credible pinch to your CV, a certification for successful completion of workshop is provided after the end of the training program, which is industry recognized.

Big Data Analytics Training Curriculum

Chapter - 2

Tableau Interface

  • Loading Data into Tableau software
  • Connecting to various databases
  • Connecting to data - Metadata, Join Types, Unions, Data Blending, Extracts
  • Understanding the Tableau interface
  • Dimensions, Measures, Pages, Filters, Marks, Rows and Columns
  • Understanding the Data Types into Tableau
  • Data Categorization into Dimensions and Measures
85.5 Hours
  • 23 Videos,
  • 1 reading,
  • 5 quizzes
  • SEE ALL
Chapter - 3

Basic Visualizations with Tableau

  • Understanding the pre-set Visualization options with Show Me
  • Basic Charts - Line Graph, Bar Graph, Pie Chart, Tree Chart, Text Tables
  • Basic Charts - Bubble charts, Scatter Charts, Circle Views
  • Line and Bar Chart
  • What are the pre-requisits for creating each type of charts?
  • Manipulation of Charts
85.5 Hours
  • 23 Videos,
  • 1 reading,
  • 5 quizzes
  • SEE ALL
Chapter - 4

Visual Analytics

  • Sorting, Grouping, Drilling Down
  • Sets
  • Filter
  • Parameters
  • Understanding Pills
85.5 Hours
  • 23 Videos,
  • 1 reading,
  • 5 quizzes
  • SEE ALL
Chapter - 5

Advance Charting Options

  • Dual Charts and Dual Axis
  • Gantt Charts
  • Box and Whiskers
  • Heat maps
  • Pareto Charts
  • Waterfall Charts
  • Diverging Bars Charts
  • Bullet Charts
  • Control Charts
  • Funnel Charts
  • Spark Lines
85.5 Hours
  • 23 Videos,
  • 1 reading,
  • 5 quizzes
  • SEE ALL
Chapter - 6

Data Analytics with Tableau

  • Forecasting
  • Clustering
  • Trend Lines
  • Reference Lines
85.5 Hours
  • 23 Videos,
  • 1 reading,
  • 5 quizzes
  • SEE ALL
Chapter - 7

Mapping

  • Introduction to Maps
  • Geocoding
  • Polygon Maps
  • Web Mapping Services
  • Backgorund Images
85.5 Hours
  • 23 Videos,
  • 1 reading,
  • 5 quizzes
  • SEE ALL
Chapter - 8

Calculations

  • Number Functions
  • Strings Functions
  • Date Functions
  • Logical Functions
  • Aggregate Functions
  • Table Calculations
85.5 Hours
  • 23 Videos,
  • 1 reading,
  • 5 quizzes
  • SEE ALL
Chapter - 9

Creating Dashboards and Stories

  • Introduction to Dashboard
  • Creating Dashboards
  • Interactive Dashboards
  • Introduction to Stories
  • Creating Stories
85.5 Hours
  • 23 Videos,
  • 1 reading,
  • 5 quizzes
  • SEE ALL
Chapter - 10

(Part B-Fundamentals of Statistics)

Objective

  • Understand the Basics of Statistics and Data Analytics
  • How the Data is structured and is Related

Topics Covered

  • Probability
  • Conditional Probability
  • Probability Distributions - Binomial, Normal, Poisson
  • Summarizing Quantitative data
  • Measures of Central Tendencies - Mean, Median, Mode
  • Skewness, Kurtosis
  • Measures of Spread - Range, Varience, Standard Deviation & Inter Quartile Range
  • Sample vs Population Parameters
  • Parametric vs Non-Parametric
  • Central Limit Theorem
  • Understanding Hypothesis
  • z Test
  • t Test
  • F Test
  • Correlation
  • Linear Regression - OLS (Ordinary Least Square), Univariate, Multivariate
  • Logistic Regression
  • Randomness of Data
85.5 Hours
  • 23 Videos,
  • 1 reading,
  • 5 quizzes
  • SEE ALL
Chapter - 12

(Part C-Machine Learning with R)

Objective

  • Understanding the Basics of Machine Learning
  • Learning R and RStudio
  • Learning Various Machine Learning Algorithms with R

Topics Covered

  • Brief history of R
  • Downloading R
  • RStudio IDE
  • Understanding the RStudio
  • Introduction to R coding
  • Packages of R
  • Basic Mathematics operators
  • Variables
  • Data Types
  • Vectors
  • Data Frames
  • Matrices
  • Arrays
  • Lists
  • Reading data from external/ internal sources
  • Creating Graphs
  • ggplot package (advance graphing capabilities)
  • Basic Statistics
  • Explorative Data Analysis (EDA)
  • Regression - Linear Model
  • Logistic Regression
  • CART (Classification & Regression Trees). Using rpart package
  • Random Forests
  • Naïve Bayes
  • kMeans
  • kNN
  • Survival Analysis
  • Text Analytics
85.5 Hours
  • 23 Videos,
  • 1 reading,
  • 5 quizzes
  • SEE ALL

Faculty

Kabir Nagpal

Ex - Consultant, Mckinsey & Co.
Certified data analyst, IIM Lucknow & Kelley Business School

Read More

Admissions

The CIBOP program is ideal for students and professionals who are interested in working in the Investment Banking industry and are keen on enhancing their domain skills.

Duration & Fees

Course

Tableau

Duration

2 months

Hours

48 Hours

Timing

1pm to 4pm (Gurugram) Sat-Sun

Fees

₹ 25,000/- plus taxes

Course

Machine Learning

Duration

4 Months

Hours

96 Hours

Timing

1pm to 4pm (Gurugram) Sat-Sun

Fees

₹ 50,000/- plus taxes

Course

Data Science (Machine Learning + Business Intelligence)

Duration

6 Months

Hours

150 Hours

Timing

1pm to 4pm (Gurugram)

Fees

₹ 70,000/- plus taxes

Who can take up this course?

Suited for candidates who are intereated to learn the concepts of Business Analytics, Machine Learning & Data Visualizations and are keen to start their career in Data Sciences. Candidates need not have any exposure about this field and can be from other backgrounds like - Mathematics, Engineering, Finance, Management , Marketing or even Human Resource. The important thing is their burning interest in learning Data Science.

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