Diploma in Business Analytics
100% JOB Assured with Globally Accepted Certificate
Intermediate
Diploma in Business Analytics
100% JOB Assured with Globally Accepted Certificate
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.
What will you learn in business analytics?
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 expose 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 suit to your domain and experience level.
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.
Business Analytics Course With Placement
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
Business Analytics Course
Unlock the power of data-driven decision-making with our comprehensive Business Analytics Course. Dive into the world of business analysis, statistical modeling, and data visualization. Master the use of popular tools and techniques for data extraction, cleaning, and analysis. Gain practical experience through hands-on projects and real-world case studies. Our industry-experienced faculty will guide you every step of the way.
In Diploma Certificate Course In Business Analytics, 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.
Unleash Success with our Certificate Course in Business Analytics
In this course you will gain an understanding of database concepts and learn to extract, manipulate, and query data using SQL. Acquiring 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 Business Analytics Course at Cranes Varsity in Bangalore, 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.
Unlock the power of data-driven decision-making and Excel in the field of data analytics with our Placement Assured Diploma program in Business Analytics course. Dive into the world of business analysis, statistical modeling, and data visualization. Master the use of popular tools and techniques for data extraction, cleaning, and analysis. Gain practical experience through hands-on projects and real-world case studies. Our industry-experienced faculty will guide you every step of the way.
In Diploma in Business Analytics Course, 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 course you will gain an understanding of database concepts and learn to extract, manipulate, and query data using SQL. Acquiring 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 Certificate in Business Analytics 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.
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.
Unlock the power of data-driven decision-making and Excel in the field of data analytics with our Placement Assured Diploma program in Business Analytics. Dive into the world of business analysis, statistical modeling, and data visualization. Master the use of popular tools and techniques for data extraction, cleaning, and analysis. Gain practical experience through hands-on projects and real-world case studies. Our industry-experienced faculty will guide you every step of the way.
In 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.
In this program you will gain an understanding of database concepts and learn to extract, manipulate, and query data using SQL. Acquiring 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.
Business Analytics Course Modules
Generic
- 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 examplesInsert, 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 normalizationOrdinal, 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, SSEPerformance Measure for Classification
- Classification Various types of classificationAccuracy,
- 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
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
Data Analytics Specialization
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
FAQs
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.
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.
