Diploma in Business Analytics

100% JOB Assured with Globally Accepted certificate

Eligibility: Diploma/BBA/B.Com.

Intermediate

Overview

Business Analytics Course

Description

Business analytics is a useful tool in the modern economy.Organizations generate huge amounts of data across industries, increasing the demand for data-literate employees who can read and analyze that data. The Diploma in Business Analytics by Cranes Varsity provides a gateway to Engineering Students,working professionals, and Corporate, as we see the growth and in-demand domain for Business Analytics

The 3.5-month Diploma in Business Analytics curriculum offers comprehensive Business Analytics knowledge and proficiency.To be a business analyst you should be good at analytical skills, and handling data, and also one should have hands-on knowledge of the latest tools and software relevant to Business Analytics. Cranes Varsity’s Business Analytics course provides the learner with all necessary tools, software, and skill sets required to master business analytics.

Cranes Varsity’s Diploma in Business Analytics is designed to cater to the Non-Engineering Graduate students and also to the Working professionals from any domain. This does not necessitate any prior knowledge of Business Analytics and/or software programming.

The Diploma in Business Analytics course is split into various modules, 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, along with this students will also learn statistical analysis techniques and basic Machine learning concepts.

After completing the course, you’ll have the ability to think like a business analyst, describing, predicting, and informing business decisions in the specific areas of marketing, human resources, finance, and operations. You’ll also have a basic understanding of data, as well as an analytical mindset that will aid you in making strategic decisions based on data.

The program content duration is for 280 hours which is designed by industry experts to be catered to the current needs of the industry. The content curated is best-in-class by leading faculties and industry leaders in the form of videos, case studies, and projects. The classroom sessions are instructor-led offline or online live mentorship sessions. Learners will be exposed to industry-relevant capstone projects during the Business Analytics course. Our Mentors are industry professionals who deliver real-world insights and have the enthusiasm to drive you as a student. They are suited to your domain and experience level.

Cranes Varsity provides a structured framework for students to learn and enhance technical skills. To make the lectures more entertaining and understandable, they are well-planned and delivered using examples. We wish to assist learners in developing a far broader range of knowledge and mental representations.

Cranes Varsity assists learners in establishing a strong career in the core domain that is aligned with their goals. We aim to improve teaching and learning processes by utilizing technology tools, whether for skill enhancement or placement of students.

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.

The program is designed to make a novice into an expert, from a learner to a Business Analytics developer. Our industry expert Trainers are multitalented and knowledgeable and have been associated with us for decades.

Candidates completing the business analytics course will get placement opportunities from various industries, such as Information Technology, Insurance and Financing, Business and professional consulting, HealthCare, and many more.

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.

Generic

  • RDBMS using MySQL
  • Python Programming
  • Exploratory Data Analysis using Pandas

Data Analytics Specialization

  • Mathematics and Statistics for Data Science
  • Machine Learning using sklearn
  • Formulating Business Analytics Problems
  • Data Analysis and Visualization using Tableau / Power BI
  • Data Analysis and Visualization using MS Excel

Projects

  • Apply statistical methods to make decisions in various business problems, including bank, stock markets, etc.
  • Apply regression
  • Apply classification
  • Use clustering to cluster banking customers
  • Computer vision projects like Face recognition, Image Quality Improvement etc.
  •  

Platform

  • Anaconda Distribution Jupyter, Spyder, MySQL
  • Tableau, Excel

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

  • NumPy
  • Slicing of Matrices
  • NumPy Functions across axis
  • Pandas Series
  • Pandas Data frame
  • Working with Categorical Data
  • Sorting Data Frames
  • Creating graphs using Matplotlib
  • Scatter Plot, Line Graph
  • Seaborn
  • Vectorization
  • Filtering
  • Stacking of arrays
  • Data Cleaning
  • Selection Data (loc, iloc)
  • Grouping & Aggregation
  • Importing csv files
  • Customizing Plots
  • Bar Graph, Histogram
  • Matplotlib
  • Broadcasting
  • Array Creation Functions
  • Matrix Calculation
  • Handling Missing Data
  • Filtering Data Frames
  • Merging Data Frame(concat, merge)
  • Importing Excel Files
  • Saving Plots
  • Subplots

Data Analytics Specialization

  • Understand what is Machine Learning
  • Supervised machine learning
  • Unsupervised machine learning
  • Data Preprocessing
  • Handling missing data
  • Onehot Encoding
  • Label encoding
  • 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
  • ML Workflow for project implementation
  • Classification
  • Various types of classification
  • Binomial and Bayes theorem
  • Logistic regression
  • Naïve Bayed Classification
  • Decision tress and its types
  • K Nearest Neighbour Classification
  • Performance Measure for Classification
  • Accuracy, Recall, Precision, Fmeasure
  • Clustering and types
  • Kmeans Clustering
  • Evaluate clustering results, Elbow Plot
  • Hierarchical clustering
  • Project implementation

  • Formulate BA problems
  • Marketing and Customer analytics
  • Financial and risk analytics
  • Preparing business presentations with BI tools
  • Analytics in Classic Business Problems
  • Business Problems with Yes/No Decisions
  • Strategy Analysis
  • Analytics in Emergent Business Problems
  • Churn in business, customer churn analysis
  • Business matrices (BCG, Ansoff)

  • 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

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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Duration: 3.5 months
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