Business Analytics and Predictive Modeling - Regression to Forecasting
What you will learn?
Build and interpret regression models for business analytics
Apply classification techniques for predictive modeling
Use decision trees for business insights
Implement time series forecasting to predict trends
Work with structured and unstructured data
About this course
🔹 About this Course:
This comprehensive course is designed to equip learners with core business analytics techniques, from regression models to time series forecasting. With hands-on learning and real-world case studies, you'll gain the expertise to make data-driven business decisions confidently.
🔹 Course Overview:
✔️ Learn fundamental to advanced analytics concepts
✔️ Hands-on exposure to Python/R for data analysis
✔️ Case studies from business, marketing, and finance
✔️ Self-paced learning with industry-recognized certification
🔹 Course Curriculum & Modules:
📌 Week 1: Introduction to Analytics
📌 Week 2: Simple Linear Regression (SLR)
📌 Week 3: Multiple Linear Regression (MLR)
📌 Week 4: Logistic Regression
📌 Week 5: Decision Trees & Unstructured Data Analysis
📌 Week 6: Forecasting & Time Series Analysis
🔹 What You Will Learn:
✔️ Build and interpret regression models for business analytics
✔️ Apply classification techniques for predictive modeling
✔️ Use decision trees for business insights
✔️ Implement time series forecasting to predict trends
✔️ Work with structured and unstructured data
🔹 Learning Objective:
🎯 Develop a strong foundation in analytics to solve real-world business problems
🎯 Gain hands-on experience with Python/R for analytics modeling
🎯 Master forecasting techniques to drive business strategies
🔹 Course Features & Benefits:
✔️ 100% self-paced with lifetime LMS access
✔️ Hands-on projects & real-world case studies
✔️ Industry-recognized certificate on completion
✔️ Access to a community of learners & mentors
✔️ Flexible payment options, including No Cost EMI
🔹 Who This Course is For:
✅ Aspiring data analysts & business analysts
✅ Marketing & finance professionals seeking data-driven insights
✅ Students & working professionals looking to enhance analytical skills
🔹 Skills Covered:
📌 Business Analytics & Data Visualization
📌 Regression & Predictive Modeling
📌 Decision Trees & Classification
📌 Time Series Forecasting
📌 Python/R for Analytics
🔹 Special Benefits to Students for Enrolling Now:
🎁 Early-bird discounts for limited-time enrollments
🎁 Free access to bonus resources & project templates
🔹 Exclusive Complimentary Benefit: One-on-One Expert Interaction
💡 Get personalized mentorship sessions with industry experts for career guidance and project assistance
🔹 Course Certificate:
📜 Earn an industry-recognized certificate upon successful completion, boosting your career prospects
🔹 Books & References:
📖 Curated reading list featuring top analytics and business intelligence books
🔹 Top Indian Companies Hiring with These Certifications & Skillsets:
🏢 TCS, Infosys, Wipro, Deloitte, Accenture, Capgemini, EY, PwC, KPMG, HCL Technologies
Suggested by top companies
Top companies suggest this course to their employees and staff.
Requirements
Basic Technology and Internet Access - A stable internet connection and the ability to use online learning platforms are essential. Students should be comfortable with navigating the course platform, accessing videos, downloading materials, and completing assessments.
Comments (0)
Decision makers often struggle with questions such as: What should be the right price for a product? Which customer is likely to default in his/her loan repayment? Which products should be recommended to an existing customer? Finding right answers to these questions can be challenging yet rewarding.
Predictive analytics is emerging as a competitive strategy across many business sectors and can set apart high performing companies. It aims to predict the probability of the occurrence of a future event such as customer churn, loan defaults, and stock market fluctuations – leading to effective business management.
Models such as multiple linear regression, logistic regression, auto-regressive integrated moving average (ARIMA), decision trees, and neural networks are frequently used in solving predictive analytics problems. Regression models help us understand the relationships among these variables and how their relationships can be exploited to make decisions.
This course is suitable for students/practitioners interested in improving their knowledge in the field of predictive analytics. The course will also prepare the learner for a career in the field of data analytics. If you are in the quest for the right competitive strategy to make companies successful, then join us to master the tools of predictive analytics.
