Diploma in Business Analytics
100% JOB Assured with Globally Accepted Certificate
Intermediate
Diploma in Business Analytics
100% JOB Assured with Globally Accepted Certificate
Overview
Certificate in Business Analytics
Description
Business Analytics Course For Working Professional
At Cranes Varsity – where we empower individuals to boost their careers with our top-rated Online/Offline Business Analytics Courses. Whether you are a working professional seeking to enhance your skills or a fresh graduate looking to enter the world of data-driven decision-making, our comprehensive program is designed to equip you with the knowledge and expertise needed to thrive in today’s data-driven business landscape.
Any person with or without analytic experience can certainly make a career transition into business analytics. While having a background in analytics or related fields can provide a head start, it is not always a prerequisite for entering the field of business analytics. While it may require some extra effort to transition into business analytics without prior experience, with determination, a willingness to learn, and a focus on acquiring the necessary skills, it is possible to establish a successful career in this field. A Business Analytics Certification Course will act as passport the industry for any interested professional.
Why Choose Our Certification Course in Business Analytics?
By completing this Business Analytics Certification Course, you will develop the skills necessary to work with data effectively, uncover valuable insights, and make data-driven decisions. These skills are highly sought after in various industries, including finance, marketing, healthcare, and more, opening up diverse career opportunities as a data analyst, business intelligence analyst, or data scientist.
In a Diploma in Business Analytics program, you will learn a diverse set of skills and knowledge essential for analyzing and interpreting business data. You will learn Database Management, Data Collection and Cleaning, Exploratory Data Analysis, Statistical Analysis, Data Visualization, Predictive Analytics, Machine Learning, Tableau and Industry case studies. This is an Online Business Analytics Course.
In this program you will gain an understanding of database concepts and learn to extract, manipulate, and query data using SQL. You will acquire hands-on experience with popular data analytics tools such as Excel, Python, and Tableau, enhancing your ability to work with and analyze data efficiently.
Our dedicated career support ensures job placement, connecting you with leading companies in the leading industries. With our strong industry connections, we provide dedicated career support and ensure job placement in leading organizations. Enroll now and pave your way to becoming a highly skilled Business Analyst.
Any person with or without analytic experience can certainly make a career transition into business analytics. While having a background in analytics or related fields can provide a head start, it is not always a prerequisite for entering the field of business analytics. While it may require some extra effort to transition into business analytics without prior experience, with determination, a willingness to learn, and a focus on acquiring the necessary skills, it is possible to establish a successful career in this field.
In a Diploma in Business Analytics program at Cranes Varsity, you will learn a diverse set of skills and knowledge essential for analyzing and interpreting business data. You will learn Database Management, Data Collection and Cleaning, Exploratory Data Analysis, Statistical Analysis, Data Visualization, Predictive Analytics, Machine Learning, Tableau and Industry case studies.
In this program you will gain an understanding of database concepts and learn to extract, manipulate, and query data using SQL. You will acquire hands-on experience with popular data analytics tools such as Excel, Python, and Tableau, enhancing your ability to work with and analyze data efficiently.
By completing a Diploma in Data Analytics, you will develop the skills necessary to work with data effectively, uncover valuable insights, and make data-driven decisions. These skills are highly sought after in various industries, including finance, marketing, healthcare, and more, opening up diverse career opportunities as a data analyst, business intelligence analyst, or data scientist.
Our dedicated career support ensures job placement, connecting you with leading companies in the leading industries. With our strong industry connections, we provide dedicated career support and ensure job placement in leading organizations. Enroll now and pave your way to becoming a highly skilled Business Analyst.
Any person with or without analytic experience can certainly make a career transition into business analytics. While having a background in analytics or related fields can provide a head start, it is not always a prerequisite for entering the field of business analytics. While it may require some extra effort to transition into business analytics without prior experience, with determination, a willingness to learn, and a focus on acquiring the necessary skills, it is possible to establish a successful career in this field.
In a Diploma in Business Analytics program at Cranes Varsity, you will learn a diverse set of skills and knowledge essential for analyzing and interpreting business data. You will learn Database Management, Data Collection and Cleaning, Exploratory Data Analysis, Statistical Analysis, Data Visualization, Predictive Analytics, Machine Learning, Tableau and Industry case studies.
In this program you will gain an understanding of database concepts and learn to extract, manipulate, and query data using SQL. You will acquire hands-on experience with popular data analytics tools such as Excel, Python, and Tableau, enhancing your ability to work with and analyze data efficiently.
By completing a Diploma in Data Analytics, you will develop the skills necessary to work with data effectively, uncover valuable insights, and make data-driven decisions. These skills are highly sought after in various industries, including finance, marketing, healthcare, and more, opening up diverse career opportunities as a data analyst, business intelligence analyst, or data scientist.
Our dedicated career support ensures job placement, connecting you with leading companies in the leading industries. With our strong industry connections, we provide dedicated career support and ensure job placement in leading organizations. Enroll now and pave your way to becoming a highly skilled Business Analyst.
Take Online Business Analytics Course from Cranes Varsity.
The Diploma in Business Analytics is a 5.5-month program that provides in-depth Business Analytics knowledge and expertise.
Cranes Varsity provides Business Analytics Course to Working Professionals.
In today’s economy, business analytics is a valuable instrument. Organizations generate huge amounts of data across industries, increasing the demand for data-literate employees who can read and analyze that data.
Multi-skilled professionals score more!
Cranes Varsity believes that with our unique technology-enabled experiential learning, we can provide high-quality learning and development solutions that directly impact important corporate performance indicators.
Cranes Varsity is happy to catalyze our distinguished clients’ advancement, and we value their credentials and testimonials.
All customer’s demands are identified, and training modules are created to meet their needs. Our training programs have a strong emphasis on creativity and innovation, which are critical for staying ahead of the competition and contributing to the industry’s long-term growth and managing and dealing with change in all aspects of the business.
Our services cover a wide range of topics, all professionally handled by a team of Learning and Development experts. All our training is Instructor-led Virtual /Classroom training with individual attention.
Cranes Varsity provides Working Professionals with a disciplined framework for learning and improving technical skills. They are well-planned and delivered using examples to make the lectures more fun and clear. We want to help working professionals build a broader set of skill development through rigorous upskill and reskill models.
Online Business Analytics Course with Placement
Cranes Varsity offers online and offline business analytics courses to help students build a solid career in the core domain connected with their objectives. We want to use digital tools to improve teaching and learning processes, whether for skill development or student placement.
Professionals can improve their expertise by taking a Certificate Course in business analytics at Cranes Varsity. At the same time, it aids in the development of their leadership abilities. This profile would be appropriate for a new business or a well-established one. Both of them require data analysis to help them build their respective companies.
What makes it even more tempting is that any professional with any background may become a business analyst and make critical decisions that alter the direction of enterprises.
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
Platform
- Anaconda Distribution Jupyter, Spyder, MySQL
- Tableau, Excel
Business Analytics Course Modules
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
Generic
Python for Data Analytics – 6 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
Exploratory Data Analysis with Pandas- 6 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
Data Analytics Specialization
Machine Learning Using SK-Learn – 6 Days
- 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
Formulating Business Analytics Problems – 8 Days
- 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)
Data Analysis and Visualization Using Tableau / Power BI * –3 Day
- 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 –3 Day
- 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
Business Analytics Course FAQs
What are the prerequisites for this Business Analytics Program?
There are no specific requirements for a Business Analytics Course, you have to be a graduate with good analytical thinking.
What kind of companies we can expect jobs from after completing this course?
As Business Analysts are required in every industry you can expect jobs from most of the top companies and others as well, as prominent recruiters like EY, Genpact, HCL, Capgemini, Deloitte, Target, etc.
What if I miss a Business Analytics lecture/session?
You will get a recorded session and also you can directly interact with the trainer and clarify your doubts
Who can join the Business Analytics Course?
Students from science, commerce, and engineering backgrounds can join, and also working professionals from any domain can join.
Testimonials
Ankita Saigal
Placed in Robert Bosch
First of all, I would like to extend my thanks to each and every member of Cranes Varsity. We were taught from the very basics of Embedded Systems Design which made it easier for students from all levels. I would like to extend my vote of thanks to cranes varsity to provide me with numerous opportunities.
Santhosh SM
Placed in L&T Technology
Cranes are one of the top embedded training institutes in Bangalore. It has been a wonderful learning experience in Cranes Varsity. The training in every module of embedded systems at Cranes was effective. It provides a good platform for embedded systems. Cranes helped me get a job in the embedded industry.
Mayur MN
Placed in L&T Technology
It was a great experience in Cranes. My dream was to get into the embedded domain. As a fresher, it is difficult to get into the Embedded Design field, but Cranes made a huge difference in my career by giving the best training and placement assistance provided by Cranes. I would like to say Cranes is the best to choose for those who dream of embedded opportunity.
Chandru V
Placed in Avin Systems
I take this opportunity to thank “CRANES VARSITY”, one of the best-embedded training institutes which are helping students to get into the best company to build their career. I thank all the trainers who enhanced my knowledge in every subject and the placement team for giving me the best opportunities in the field of embedded. Thank you for all your support.
Hemanth Kumar
Placed in Caravel Info Systems
Cranes varsity is the best Embedded Training Institute to learn both practical and theoretical knowledge. It is the best place to gear up your career in a core embedded industry. Management and faculty member support till you get placed. They provided lots of opportunities to me. The embedded Course modules that we learnt here are systematic, and I immensely earned great knowledge.
Ankit Ahalawat
Placed in AK Aerotek Software
I am happy for Cranes for giving a platform and providing opportunities for attending the interview. Modules test, Mock test really helps to clear any company written test/ interview. Trainers were excellent at explaining and clarifying the doubts. I am very thankful to Cranes Varsity.
Nithin G
Placed in Moschip Semiconductor
Cranes varsity is the best platform to improve your technical skills in Embedded System Design. Their dedication towards teaching modules and interaction with the students is commendable, which made me achieve good skills for my career growth in the electronics/semiconductor industry.
Amitha Pankaj
Placed in Lekha Wireless
Happy to say that I am placed in Lekha Wireless. Cranes are one of the best Embedded Training Institutes. The way of teaching in Cranes is good. I thank the management and faculty for the guidance and opportunity.
Sidharth S
Placed in L&T Technology
If not Cranes, I would have been doing a job of not my interest and passion. Cranes provided me with the platform to start my career and knowledge about corporate life and requirements. “Thank you, Cranes” would be an understatement.
