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IBM
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Business Analytics
Business Analytics
Turn Data into Decisions: Master Business Analytics in less than a semester.
Turn Data into Decisions: Master Business Analytics in less than a semester.
Turn Data into Decisions: Master Business Analytics in less than a semester.
DURATION
3 months
Intensive
MODE
LIVE Online
Intensive
FORMAT
Hybrid
Hands-on, Theoretic
STARTING
December, 2024
Program Details
Program Details
Program Details
Our Business Analytics Pre-Graduation program equips you with the most sought-after skills and tools in today's data-driven world. Master data manipulation, analysis, and visualization using industry-standard software like Tableau or Power BI. Dive into machine learning with libraries like scikit-learn or TensorFlow. Sharpen your Python or R programming abilities and explore big data analytics tools like Hadoop or Spark. Gain hands-on experience through 10+ industry projects, putting your newfound knowledge into action. Don't wait until graduation – kickstart your career in Business Analytics today!
Our Business Analytics Pre-Graduation program equips you with the most sought-after skills and tools in today's data-driven world. Master data manipulation, analysis, and visualization using industry-standard software like Tableau or Power BI. Dive into machine learning with libraries like scikit-learn or TensorFlow. Sharpen your Python or R programming abilities and explore big data analytics tools like Hadoop or Spark. Gain hands-on experience through 10+ industry projects, putting your newfound knowledge into action. Don't wait until graduation – kickstart your career in Business Analytics today!
Our Business Analytics Pre-Graduation program equips you with the most sought-after skills and tools in today's data-driven world. Master data manipulation, analysis, and visualization using industry-standard software like Tableau or Power BI. Dive into machine learning with libraries like scikit-learn or TensorFlow. Sharpen your Python or R programming abilities and explore big data analytics tools like Hadoop or Spark. Gain hands-on experience through 10+ industry projects, putting your newfound knowledge into action. Don't wait until graduation – kickstart your career in Business Analytics today!
Who should enroll?
Who should enroll?
Who should enroll?
-You have an interest in business analytics and want to start your journey.
-You aim to make your profile more attractive to employers in data-driven roles.
-You want to enhance your academic background with practical analytics skills.
-You are considering a transition to a business analytics career.
-You enjoy analyzing data to find solutions to complex business problems.
-You have an interest in business analytics and want to start your journey.
-You aim to make your profile more attractive to employers in data-driven roles.
-You want to enhance your academic background with practical analytics skills.
-You are considering a transition to a business analytics career.
-You enjoy analyzing data to find solutions to complex business problems.
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TEACHING PLAN (3 Month Program)
Week 1
Session 1: Introduction to Business Analytics
- Definition and importance of business analytics
- Key concepts and terminology in business analytics
Session 2: Data Collection and Data Types
- Overview of data collection methods and sources
- Understanding different types of data (structured, unstructured, and semi-structured)
Session 3: Data Cleaning and Preparation
- Techniques for cleaning and preprocessing data
- Handling missing values, outliers, and data inconsistencies
Week 1
Session 1: Introduction to Business Analytics
- Definition and importance of business analytics
- Key concepts and terminology in business analytics
Session 2: Data Collection and Data Types
- Overview of data collection methods and sources
- Understanding different types of data (structured, unstructured, and semi-structured)
Session 3: Data Cleaning and Preparation
- Techniques for cleaning and preprocessing data
- Handling missing values, outliers, and data inconsistencies
Week 1
Session 1: Introduction to Business Analytics
- Definition and importance of business analytics
- Key concepts and terminology in business analytics
Session 2: Data Collection and Data Types
- Overview of data collection methods and sources
- Understanding different types of data (structured, unstructured, and semi-structured)
Session 3: Data Cleaning and Preparation
- Techniques for cleaning and preprocessing data
- Handling missing values, outliers, and data inconsistencies
Week 2
Session 4: Exploratory Data Analysis (EDA)
- Exploring and summarizing data using descriptive statistics)
- Visualizing data through charts, graphs, and plots
Session 5: Statistical Analysis for Business Analytics)
- Statistical techniques for analyzing business data
- Hypothesis testing, correlation, and regression analysis
Session 6: Predictive Analytics and Regression Models
- Introduction to predictive analytics and its applications in business
- Building and interpreting regression models for predictive analysis
Week 2
Session 4: Exploratory Data Analysis (EDA)
- Exploring and summarizing data using descriptive statistics)
- Visualizing data through charts, graphs, and plots
Session 5: Statistical Analysis for Business Analytics)
- Statistical techniques for analyzing business data
- Hypothesis testing, correlation, and regression analysis
Session 6: Predictive Analytics and Regression Models
- Introduction to predictive analytics and its applications in business
- Building and interpreting regression models for predictive analysis
Week 2
Session 4: Exploratory Data Analysis (EDA)
- Exploring and summarizing data using descriptive statistics)
- Visualizing data through charts, graphs, and plots
Session 5: Statistical Analysis for Business Analytics)
- Statistical techniques for analyzing business data
- Hypothesis testing, correlation, and regression analysis
Session 6: Predictive Analytics and Regression Models
- Introduction to predictive analytics and its applications in business
- Building and interpreting regression models for predictive analysis
Week 3
Session 7: Classification and Decision Trees
- Overview of classification algorithms for categorical data analysis
- Building decision tree models for classification tasks
Session 8: Cluster Analysis and Market Segmentation
- Understanding clustering techniques for customer segmentation
- Analyzing customer behavior and preferences through clustering
Session 9: Time Series Analysis and Forecasting
- Basics of time series data analysis
- Forecasting future trends and patterns using time series models
Week 3
Session 7: Classification and Decision Trees
- Overview of classification algorithms for categorical data analysis
- Building decision tree models for classification tasks
Session 8: Cluster Analysis and Market Segmentation
- Understanding clustering techniques for customer segmentation
- Analyzing customer behavior and preferences through clustering
Session 9: Time Series Analysis and Forecasting
- Basics of time series data analysis
- Forecasting future trends and patterns using time series models
Week 3
Session 7: Classification and Decision Trees
- Overview of classification algorithms for categorical data analysis
- Building decision tree models for classification tasks
Session 8: Cluster Analysis and Market Segmentation
- Understanding clustering techniques for customer segmentation
- Analyzing customer behavior and preferences through clustering
Session 9: Time Series Analysis and Forecasting
- Basics of time series data analysis
- Forecasting future trends and patterns using time series models
Week 4:
Session 10: Data Mining and Association Rules
-Introduction to data mining concepts and techniques
-Extracting actionable insights through association rule mining
Session 11: Text Mining and Sentiment Analysis
-Analyzing textual data for sentiment analysis
-Techniques for extracting meaning and sentiment from unstructured text
Session 12: Optimization and Linear Programming
-Overview of optimization models and linear programming
-Applying optimization techniques to business decision-making
Week 4:
Session 10: Data Mining and Association Rules
-Introduction to data mining concepts and techniques
-Extracting actionable insights through association rule mining
Session 11: Text Mining and Sentiment Analysis
-Analyzing textual data for sentiment analysis
-Techniques for extracting meaning and sentiment from unstructured text
Session 12: Optimization and Linear Programming
-Overview of optimization models and linear programming
-Applying optimization techniques to business decision-making
Week 4:
Session 10: Data Mining and Association Rules
-Introduction to data mining concepts and techniques
-Extracting actionable insights through association rule mining
Session 11: Text Mining and Sentiment Analysis
-Analyzing textual data for sentiment analysis
-Techniques for extracting meaning and sentiment from unstructured text
Session 12: Optimization and Linear Programming
-Overview of optimization models and linear programming
-Applying optimization techniques to business decision-making
Week 5
Session 13: Simulation Modeling and Analysis
-Basics of simulation modeling for business scenarios
-Analyzing complex systems and making informed decisions through simulations
Session 14: Data Visualization and Storytelling
-Principles of effective data visualization for business analytics
-Creating compelling visualizations to communicate insights and tell data-driven stories
Session 15: Dashboard Design and Interactive Reporting
-Designing interactive dashboards for data exploration and reporting
-Creating visually appealing and user-friendly dashboards using visualization tools
Week 5
Session 13: Simulation Modeling and Analysis
-Basics of simulation modeling for business scenarios
-Analyzing complex systems and making informed decisions through simulations
Session 14: Data Visualization and Storytelling
-Principles of effective data visualization for business analytics
-Creating compelling visualizations to communicate insights and tell data-driven stories
Session 15: Dashboard Design and Interactive Reporting
-Designing interactive dashboards for data exploration and reporting
-Creating visually appealing and user-friendly dashboards using visualization tools
Week 5
Session 13: Simulation Modeling and Analysis
-Basics of simulation modeling for business scenarios
-Analyzing complex systems and making informed decisions through simulations
Session 14: Data Visualization and Storytelling
-Principles of effective data visualization for business analytics
-Creating compelling visualizations to communicate insights and tell data-driven stories
Session 15: Dashboard Design and Interactive Reporting
-Designing interactive dashboards for data exploration and reporting
-Creating visually appealing and user-friendly dashboards using visualization tools
Week 6
Session 16: Business Intelligence and Data Warehousing
- Understanding the role of business intelligence in analytics
- Basics of data warehousing for storing and accessing business data
Session 17: Data Governance and Privacy
- Ensuring data governance and compliance with privacy regulations
- Ethical considerations in handling and analyzing business data
Session 18: Project Management in Analytics
- Project management principles for analytics projects
- Planning, executing, and delivering successful analytics projects
Week 6
Session 16: Business Intelligence and Data Warehousing
- Understanding the role of business intelligence in analytics
- Basics of data warehousing for storing and accessing business data
Session 17: Data Governance and Privacy
- Ensuring data governance and compliance with privacy regulations
- Ethical considerations in handling and analyzing business data
Session 18: Project Management in Analytics
- Project management principles for analytics projects
- Planning, executing, and delivering successful analytics projects
Week 6
Session 16: Business Intelligence and Data Warehousing
- Understanding the role of business intelligence in analytics
- Basics of data warehousing for storing and accessing business data
Session 17: Data Governance and Privacy
- Ensuring data governance and compliance with privacy regulations
- Ethical considerations in handling and analyzing business data
Session 18: Project Management in Analytics
- Project management principles for analytics projects
- Planning, executing, and delivering successful analytics projects
Download Complete 3 Months Plan
Download Complete 3 Months Plan
CAREER DEVELOPMENT TRACK
Pregrad Career Assist Access
Mentoring
career-specific resume tailoring
Personal Branding
Build and showcase your skills in public
Strategic LinkedIn profiling
Community Session
Strengthen Communication
Improve presentation skills
Interview Preparation
Mock community sessions & GD
Art of negotiation
Domain workshops/Masterclasses
Masterclasses from professionals
HR Session
Career Kick-start
Internship/Freelance/ Applications & Interview
Placement assistance in final year
Total Fee of the Program
₹ 20060/- Including tax
(Non-refundable)
0% cost EMI Option Available*
EMI options for admission will not be available on discounted Fee or admission through scholarship
Live Learning delivered by Industry veteran
Sessions Backup
Hands-On Projects & Challenges
Global Certifications
Access to Career Assist cell*
Payment gateway Razorpay
FAQ
Is this course for Beginner, Intermediate, and Advanced level?
What is the duration of this Program?
Is it possible to shift my batch?
Is this course for Beginner, Intermediate, and Advanced level?
What is the class schedule for the Program?
Will I be provided with recordings of classes and how long will we have access to it?
What is the role of the mentor?
What are the profiles of the mentors?
How often does the new Batch start?
When will we be getting internship opportunities?
How is placement at Pregrad?
What is the success rate of the Pregrad's Pre-graduation Program?
Is this course for Beginner, Intermediate, and Advanced level?
What is the duration of this Program?
Is it possible to shift my batch?
Is this course for Beginner, Intermediate, and Advanced level?
What is the class schedule for the Program?
Will I be provided with recordings of classes and how long will we have access to it?
What is the role of the mentor?
What are the profiles of the mentors?
How often does the new Batch start?
When will we be getting internship opportunities?
How is placement at Pregrad?
What is the success rate of the Pregrad's Pre-graduation Program?
Is this course for Beginner, Intermediate, and Advanced level?
What is the duration of this Program?
Is it possible to shift my batch?
Is this course for Beginner, Intermediate, and Advanced level?
What is the class schedule for the Program?
Will I be provided with recordings of classes and how long will we have access to it?
What is the role of the mentor?
What are the profiles of the mentors?
How often does the new Batch start?
When will we be getting internship opportunities?
How is placement at Pregrad?
What is the success rate of the Pregrad's Pre-graduation Program?
G Block Sector 6, Noida, Uttar Pradesh - 201301
hello@pregrad.in
+91 9971300194
G Block Sector 6, Noida, Uttar Pradesh - 201301
hello@pregrad.in
+91 9971300194