POP on Business Analytics

Eligibility – Pursuing Graduates B.E/ B.Tech

Intermediate

Overview

Business Analytics Course With Placement

In today’s fast-paced business world, data is the driving force behind success. Our Business Analytics Course With Placement is meticulously designed to empower you with the ability to unravel complex data, extract valuable insights, and drive growth. Whether you’re a recent graduate or a professional looking to upskill, our course caters to diverse backgrounds and paves the way for a data-focused career.

The Placement Oriented Program on Business Analytics at Cranes Varsity is a highly specialized training program designed to equip students with the skills and knowledge required to excel in the field of business analytics. With a strong emphasis on practical training and industry relevance, this program prepares students for successful careers in data-driven decision-making.

The curriculum of the program covers a wide range of topics essential to business analytics, including data visualization, statistical analysis, predictive modeling, data mining, data storytelling, and business intelligence. Students learn how to collect, analyze, and interpret data to derive valuable insights and make informed business decisions. The program also focuses on using popular analytics tools and software to work with real-world data sets.

Why Choose Our Business Analytics Certification Program?

At Cranes Varsity, we understand that the modern business landscape thrives on data. Our Business Analytics Certification Course is meticulously crafted to equip you with the skills, knowledge, and practical experience needed to navigate this data-rich environment with confidence.

Cranes Varsity understands the importance of industry collaboration in the field of business analytics. As such, the institute maintains strong partnerships with leading companies and industry experts. This collaboration facilitates guest lectures, workshops, and industry visits, providing students with exposure to the latest trends and technologies in the field. It also opens doors to internship opportunities and potential job placements.

To enhance students’ employability, the program also focuses on developing essential soft skills, such as communication, critical thinking, and problem-solving. Students receive guidance on resume building, interview preparation, and career counseling, ensuring they are well-prepared for the job market. The dedicated placement cell at Cranes Varsity assists students in connecting with industry recruiters and organizing placement drives, maximizing their chances of securing lucrative job offers in top analytics firms.

By enrolling in the Placement Oriented Program on Business Analytics, students gain a strong foundation in business analytics concepts, along with practical experience and industry exposure. This program prepares them for roles such as business analyst, data analyst, data scientist, or analytics consultant. With a focus on practical training, industry collaboration, and job placement, this program equips students with the skills they need to thrive in the dynamic and evolving field of business analytics.

Business Analytics Course Content

Relational Database - SQL –20 hrs
  • Introduction to databases and RDBMS,
  • Database creation, concept of relation and working examples Creating tables.
  • Design view of the table, Alter table operations & Key Constraints
  • Read, update and delete operations on tables. Working with nulls
  • Querying tables: Select statement, examples and its variations
  • Filtering, Sorting, Predicates and working examples
  • Joins in SQL and working examples
  • Insert, Update, Delete operations and working examples Scalar functions in SQL and working examples
  • SQL set based operations and data aggregation
  • Sub-queries in SQL       
  • Normalization and de-normalization: Views and Temporary tables
  • Transactions in SQL
  • SQL programming
  • Creating stored procedures, Cursors in SQL
  • EBS(Elastic Block Storage),VPC
  • EBS volumes and Snapshots
  • RDS
Python Programming - 20 hrs
  • Introduction to Python
  • Python Data types and Conditions
  • Control Statements
  • Python Functions Default arguments
  • Functions with variable number of args
  • Scope of Variables
  • Global specifier
  • Working with multiple files
  • List and Tuple
  • List Methods
  • List Comprehension
  • Map and filter functions
  • String
  • List comprehension with conditionals
  • Set and Dictionary
  • Exception Handling
  • File Handling
  • Business Analytics Specialization
Exploratory Data Analysis with Pandas- 20 hrs
  • NumPy
  • Vectorization
  • Broadcasting
  • Slicing of Matrices
  • Filtering Array Creation Functions
  • NumPy Functions across axis
  • Stacking of arrays
  • Matrix Calculation
  • Pandas Series
  • Data Cleaning
  • Handling Missing Data
  • Pandas Data frame
  • Selection Data (loc, iloc)
  • Filtering Data Frames
  • Working with Categorical Data
  • Grouping & Aggregation
  • Merging Data Frame(concat, merge)
  • Sorting Data Frames
  • Importing csv files
  • Importing Excel Files
  • Creating graphs using Matplotlib
  • Customizing Plots
  • Saving Plots
  • Scatter Plot, Line Graph
  • Bar Graph, Histogram
  • Subplots
  • Seaborn
  • Matplotlib
Foundational Statistics - 10 hrs
  • Logarithm
  • Python Scipy Library
  • Mean Absolute Deviation,
  • Standard Deviation
  • Probability and Distribution
  • Normal Distribution and Z Score
  • Descriptive and Inferential Statistics
  • Binomial Theorem
  • Visualizing Data
  • Mean, Median, Mode
  • Hypothesis testing
  • Variance: ANOVA
  • Percentile,
  • Inferential Statistics
  • Statistical Significance
  • Log Normal Distribution
  • Chi-square test, T test
  • Data Preprocessing
  • Standardization and normalization
  • Ordinal, frequency encoding
  • Transformation
Foundational Machine learning – 16 hrs
  • Understand what is Machine Learning
  • Regression
  • Logistic regression
  • Supervised machine learning
  • Simple linear regression
  • Naïve Bayed Classification
  • Unsupervised machine learning
  • Multiple linear regression
  • Decision tress and its types
  • Train test split the data
  • Performance measure for regression
  • K Nearest Neighbour Classification
  • ML Workflow for project implementation
  • MSE, R-Squared, MAE, SSE
  • Performance Measure for Classification
  • Classification Various types of classification
  • Accuracy,
  • Recall, Precision, Fmeasure
Data Analysis and Visualization Using Tableau – 24 hrs
  • Tableau Introduction
  • Traditional Visualization vs Tableau
  • Tableau Architecture
  • Working with sets
  • Creating Groups
  • Data types in Tableau
  • Connect Tableau with Different Data Sources
  • Visual Analytics Parameter Filters
  • Cards in Tableau Charts, Dash-board
  • Joins and Data Blending
  • Tableau Calculations using Functions
  • Building Predictive Models
  • Dynamic Dashboards and Stories
Data Analysis and Visualization Using Excel –10 hrs
  • Introduction to excel
  • Viewing, Entering, and Editing Data
  • Introduction to Data Quality
  • Intro to Analyzing Data Using Spreadsheets
  • Converting Data with Value and Text
  • Apply logical operations to data using IF
  • Charting techniques in Excel
  • Interactive dashboard creation
  • Data analytics project using Excel

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Duration: 5 months (At Cranes Varsity) 250hrs (At College Premises)
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