Diploma in Business Analytics

100% JOB Assured with Globally Accepted Certificate

Eligibility: BE, B.Tech, ME, M.Tech

Overview

Study Business Analytics and become a game-changer

Description

The connected world we live in today generate huge amount of data. To derive meaningful insights from the data is a skill that is in high demand across industries. The Diploma in Business Analytics by Cranes Varsity is a gateway for Engineering students, non-Engineering graduates and working professionals from any domain to start a flying career in Business Analytics. This course does not necessitate any prior knowledge of Business Analytics and/or Software Programming.

Comprehensive Curriculum
The 3.5-month Diploma in Business Analytics curriculum offers comprehensive Business Analytics knowledge and proficiency. It will empower you with good analytical skills and make you adept in handling data. You will also gain hands-on knowledge on the latest tools and software relevant to Business Analytics.

The Diploma in Business Analytics course is split into various modules and the students will go through these modules stage by stage with regular assessments. Modules covered include Databases management with SQL, Python programming, and Data analysis using EXCEL and TABLEAU. That apart, students will also learn statistical analysis techniques and basic Machine Learning concepts.

A Business Analytics Course Curated by Industry Experts
Cranes Varsity’s Business Analytics Course is curated industry leaders and leading faculty. It includes videos, case studies and projects. Duration of the course is 280 hours and consists of instructor-led online or offline classroom sessions and online live mentorship. Students will be exposed to industry-relevant capstone projects and by the end of the course will be able to think like a business analyst – describing, predicting and informing business decisions in the specific areas of marketing, HR, finance, and operations. They will also develop an analytical mindset that will aid in making strategic decisions based on data.

Business Analytics Course with Placement
Cranes Varsity assists learners in establishing a strong career in the core domain that is aligned with their goals. We offer the highest quality teaching, assessment, and placement support through our Business Analytics courses. To support the students in cracking the interviews, Cranes Varsity provides resume building & interview readiness through defined soft skills and aptitude training from industry experts.

Candidates completing the business analytics course will get placement opportunities across industries including Information Technology, Insurance and Financing, Business and Professional Consulting, and Health Care, among others.

If you want to start a career in Business Analytics and want to acquire Business Analytics Training, Certification, and Placement, Cranes Varsity is the right place to be.

Business Analytics Course Modules

Generic

  • Introduction to Python
  • Python Functions
  • Scope of Variables
  • List and Tuple
  • Map and filter functions
  • Set and Dictionary
  • Python Data types and Conditions
  • Default arguments
  • Global specifier
  • List Methods
  • String
  • Exception Handling
  • Control Statements
  • Functions with variable number of args
  • Working with multiple files
  • List Comprehension
  • List comprehension with conditionals
  • File Handling

Data Analytics Specialization:

  • Logarithm
  • Standard Deviation
  • Descriptive and Inferential Statistics
  • Linear Algebra
  • Differential Calculus
  • Chain Rule
  • Python Scipy Library
  • Mean, Median, Mode
  • Percentile
  • Log Normal Distribution
  • PCA: principle component Analysis
  • Probability and Distribution
  • Binomial Theorem
  • Hypothesis testing
  • Mean Absolute Deviation
  • Normal Distribution and Z Score
  • Visualizing Data
  • Variance: ANOVA
  • Statistical Significance
  • Inferential Statistics
  • Chi-square test, T test
  • Ordinal, frequency encoding
  • Mean Absolute Deviation
  • Normal Distribution and Z Score
  • Visualizing Data
  • Variance: ANOVA
  • Statistical Significance
  • Data Preprocessing
  • Transformation

  • Understand what is Machine Learning
  • Supervised Machine Learning
  • Unsupervised Machine Learning
  • Train test split the data
  • ML Workflow for project implementation
  • Classification
  • Regression
  • Ordinal, frequency encoding
  • Standardization and normalization
  • Train test split the data
  • K fold cross validation
  • Regression
  • Simple linear regression
  • Multiple linear regression
  • Performance measure for regression
  • MSE, R-Squared, MAE, SSE
  • Feature selection for Regression
  • MSE, R-Squared, MAE, SSE
  • Various types of classification
  • Logistic regression
  • Naïve Bayed Classification
  • Decision tress and its types
  • K Nearest Neighbour Classification
  • Performance Measure for Classification
  • Accuracy, Recall, Precision, Fmeasure

  • Tableau Introduction
  • Working with sets
  • Connect Tableau with Different Data Sources
  • Cards in Tableau
  • Tableau Calculations using Functions
  • Traditional Visualization vs Tableau
  • Creating Groups
  • Visual Analytics
  • Charts, Dash-board
  • Building Predictive Models
  • Tableau Architecture
  • Data types in Tableau
  • Parameter Filters
  • Joins and Data Blending
  • Dynamic Dashboards and Stories

  • Introduction to Excel
  • Intro to Analyzing Data Using Spreadsheets
  • Charting techniques in Excel
  • Viewing, Entering, and Editing Data
  • Converting Data with Value and Text
  • Interactive dashboard creation
  • Introduction to Data Quality
  • Apply logical operations to data using IF
  • Data analytics project using Excel

  • Title selection
  • Final results
  • Dataset Selection
  • Report submission
  • Interim results

Placement Statistics

FAQs

This course enables you to apply for various job roles like business analyst, data analyst, and business intelligence with high pay packages, your career path will also be bright

Every company needs business as they coordinate with various teams within the organization to help identify issues and fix them, completing this course enables you to apply for highly in-demand jobs.

SQL, Python programming, Microsoft Excel, Tableau, statistical analysis, and basics of machine learning

NO, programming knowledge is not mandatory but having one is an advantage.

Projects like customer analysis, insurance risk analysis, and also projects related to finance and marketing are included, students are open to choose their own projects.

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