Diploma in Business Analytics
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Overview
Learn Business Analytics for a Dream Career
Description
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.
Business Analytics Course Modules
- RDBMS using MySQL
- Python Programming
- Exploratory Data Analysis using Pandas
- 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
- Apply statistical methods to make decisions in various business problems, including bank, stock markets, etc.
- Apply regression to predict future flight price
- Apply classification to classify customer
- Use clustering to cluster banking customers
- Computer vision projects like Face recognition, Image Quality Improvement, etc.
- Anaconda Distribution Jupyter, Spyder, MySQL
- Tableau, Excel
Course Content
Generic:
Relational Database – SQL – 10 Days
- Introduction to databases and RDBMS
- Read, update and delete operations on tables. Working with nulls
- Joins in SQL and working examples
- SQL set based operations and data aggregation, Sub-queries in SQL
- EBS(Elastic Block Storage),VPC
- Database creation, concept of relation and working examples
- Querying tables: Select statement, examples and its variations
- Insert, Update, Delete operations and working examples
- Normalization and de-normalization: Views and Temporary tables, Transactions in SQL
- EBS volumes and Snapshots
- Creating tables. Design view of the table, Alter table operations & Key Constraints
- Filtering, Sorting, Predicates and working examples
- Scalar functions in SQL and working examples
- SQL programming, Creating stored procedures, Cursors in SQL
- RDS
Python for Data Analytics – 10 Days
- 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
Business Analytics Specialization:
Exploratory Data Analysis with Pandas – 10 Days
- 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
Foundational Statistics – 5 Days
- 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
Foundational Machine learning – 7 Days
- 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
Data Analysis and Visualization Using Tableau / Power BI * – 7 Days
- 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
Data Analysis and Visualization Using Excel – 7 Days
- 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
Capstone Project: 5 Days
- Title selection
- Final results
- Dataset Selection
- Report submission
- Interim results
Placement Statistics
Embedded Training Course FAQs
What is Business Analytics?
Business analytics uses data to form business insights and recommend changes in businesses, typical people handling this takes are called business analysts.
What are the benefits of this Business Analytics Course?
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
Is the Business Analytics Certification Course worth it?
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.
What important skills will you learn with this Business Analytics Course?
SQL, Python programming, Microsoft Excel, Tableau, statistical analysis, and basics of machine learning
Is programming knowledge a prerequisite for a Business Analytics Course?
NO, programming knowledge is not mandatory but having one is an advantage.
What projects are included in this Business Analytics Course in Bangalore?
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.