Get updates on Eligibility, Admission, Placements Fees Structure
Quick Facts
| Medium Of Instructions | Mode Of Learning | Mode Of Delivery |
|---|---|---|
| English | Self Study | Video and Text Based |
Course Overview
The Business Intelligence & Analytics certification course offers a comprehensive curriculum such as Business Intelligence & Analytics (BIA), technical architecture, case analysis of AT&T long distance, databases, SQL queries, data warehousing, OnLine Analytical Processing (OLAP), and others. Students gain hands-on training from industry experts, helping them to function effectively on real-world projects.
The certification course focuses on covering important modelling techniques such as regression, decision trees, clustering, ANN, and text mining. The Business Intelligence & Analytics certification by NPTEL is 12 weeks course. The prerequisite for this certification course is a core course on Business statistics. The students gain in-depth knowledge of the principles and techniques used in the industry.
Also Read: Online Business Intelligence Courses & Certifications
The Highlights
- 12 Weeks to Complete
- Completion Certification
- Certification by IIT
Programme Offerings
- Hands-on Learning
- videos
Courses and Certificate Fees
| Certificate Availability | Certificate Providing Authority |
|---|---|
| yes | IIT Madras (IITM) |
Eligibility Criteria
Academic Qualifications
The Business Intelligence & Analytics certification course prerequisites is a core course on Business statistics.
Certification Qualifying Details
You will receive a certificate upon completion of the Business Intelligence & Analytics certification course.
What you will learn
After completing the Business Intelligence & Analytics certification syllabus, the students will gain insights into Business Intelligence and Analytics, and tree implementation in Python. The students will also learn the required knowledge and skills on the thought process, modelling approaches, and tools that are needed to use data from the enterprise databases and other sources.
The students will also gain in-depth knowledge in data mining, and modelling techniques like regression, clustering, ANN, and text mining. The Business Intelligence & Analytics training prepares the students for business analytics, data science, and market research careers. This certification supports various industries such as analytics and data science, IT services, manufacturing and services, operations and marketing.
Who it is for
The Business Intelligence & Analytics online course is beneficial for data science, business analytics, and market research. Aspiring students interested in business intelligence and analytics can obtain this course to enhance their skills and knowledge. This course can also be beneficial for:
Admission Details
To join the Business Intelligence & Analytics classes, follow these steps:
Step 1: Click the link below:
https://nptel.ac.in/courses/106106361
Step 2: Candidates need to create a separate account or Log In with a Microsoft Account or Google account and Sign In with the credentials.
Step 3: Once the candidates Logged In, they can enroll for the course by filling out the required information and submitting the form and joining the course.
The Syllabus
- Introduction to Business Intelligence & Analytics (BIA)
- Drivers of BIA
- Types of analytics: descriptive to prescriptive
- Vocabulary of business analytics
- Course plan and resources
- Technical architecture of BIA
- Case analysis of AT&T Long distance
- Fundamentals of data management
- OnLine Transaction Processing (OLTP)
- Design process of databases
- Relational databases
- Normalisation
- SQL queries
- ShopSense case of management questions
- Data warehousing
- OnLine Analytical Processing (OLAP)
- Data cube
- Descriptive analytics
- and visualization
- Customer analytics
- Survival analysis
- Customer lifetime value
- Case study
- Data mining process
- Introduction to statistical learning
- Data pre-processing, data quality
- Overview of data mining techniques
- Case study using regression analysis
- Introduction to classification
- Classification techniques
- Scoring models
- Classifier performance
- ROC and PR curves
- Introduction to decision trees
- Tree induction
- Measures of purity
- Tree algorithms
- Pruning
- Ensemble methods
- Tree implementation in Python: problem of targeted mailing
Cluster analysis, measures of distance, clustering algorithms, K-means and other techniques, cluster quality
- A store segmentation case study using clustering
- Implementation in Python
- Profiling clusters
- Cluster interpretation and actionable insights
- RFM sub- segmentation for customer loyalty
- Machine learning,
- Artificial Neural Networks (ANN)
- Topology and training algorithms
- Back propagation
- Financial time series modelling using ANN
- Implementation in Python
- Text mining, process
- Key concepts
- Sentiment scoring
- Text mining using R-the case of a movie discussion forum summary