Get updates on Eligibility, Admission, Placements Fees Structure
Quick Facts
| Medium Of Instructions | Mode Of Learning | Mode Of Delivery | Frequency Of Classes |
|---|---|---|---|
| English | Self Study, Virtual Classroom | Video and Text Based | Weekdays |
Course Overview
The Online Programme on Big Data and AI Techniques by FORE School of Management aims to explore Big Data Analytics techniques and enable learners to apply it in their research work or teaching. The programme focuses more on practice than theory, and as such, learners will have to undertake several practical assignments.
The Online Programme on Big Data and AI Techniques Training is 40 hours long and spread across six weeks. Therefore, learners will have to devote around six hours to the programme each week. Classes are live on weekdays between 2 PM and 5 PM. They can also indulge in real-time interactions with the course educators, clarifying all their doubts and queries.
For the practical exercises that are part of the Online Programme on Big Data and AI Techniques Certification Syllabus, learners need laptops with at least 4 GB RAM. The student and the teacher will work on their respective laptops and simultaneously solve each assignment. Even though it is an online programme, the learning experience is as if the teacher and the students are in a laboratory working together.
The Highlights
- Online Curriculum
- KNIME workflow
- Theoretical lessons
- 40-Hour Training
- Six-Week Course
- Practical Assignments
- Interactive Programme
- Clarifying Doubts in Real-Time
- FORE School of Management
Programme Offerings
- Online Course
- 40-Hour Training
- Six-week Course
- practical assignments
- Interactive Programme
- Clarify Doubts in Real-Time
- FORE School of Management Course
Courses and Certificate Fees
| Certificate Availability | Certificate Providing Authority |
|---|---|
| yes | FSM Delhi |
Eligibility Criteria
As prerequisites for the Online Programme on Big Data and AI Techniques training, students must have a 4GB RAM laptop and complete the weekly practical exercises.
What you will learn
After completing the Online Programme on Big Data and AI Techniques Training, learners should be thorough with:
- Feature Importance and Data Visualization (Mosaic Plots, Parallel Coordinates, and T-SNE)
- Supervised and Unsupervised Learning Techniques
- Automated Machine Learning Using H2O
- Regression and Classification
- Deep Learning Techniques
- Dimensionality Reduction
- Anomaly Detection
Admission Details
Step 1: Clicking on this link will direct you to the Online Programme on Big Data and AI Techniques page on the FORE School of Management website.
https://www.fsm.ac.in/online-programme-on-big-data-and-ai-techniques
Step 2: Keep scrolling down till you find the ‘Enquire Now’ button; click on it.
Step 3: Enter your full name, the name of your organization, your email address, and mobile number, and again click on ‘Enquire Now’.
Step 4: A representative from the FORE School of Management will get in touch with you and give you further instructions.
Application Details
Initially, candidates will not have to fill out an application form. However, they must fill out an Enquiry Form to express their interest in the Online Programme on Big Data and AI Techniques certification course.
Aspirants need to enter their full name, email address, mobile number, and the organization name. A representative from the FORE School of Management will then get in touch with them, and give them further instructions.
The Syllabus
- Kmeans clustering
- Hierarchical clustering
- DBScan algorithm
- Expectation-Maximization algorithm
- T-SNE manifold learning technique
- Principal Component Analysis
- Random Projections
- Decision trees
- Ensemble modeling using Random Forest
- Gradient Boosting Techniques
- Adaboost
- Gradient Boosting Learner
- XGBoost
- Handling imbalanced data—SMOTE and ADASYN
- Performance measures:
- Accuracy
- Precision and Recall
- F-measure
- Area Under the Curve
- Cohen’s Kappa
- Sensitivity
- Specificity
- Neural Networks
- Deep Learning models using H2O
- Anomaly detection using isolation forests
- Autoencoders
FSM Delhi Frequently Asked Questions (FAQ's)
This course’s hardware requirements include a laptop with at least 4 GB RAM.
No, classes are live on weekdays, between 2 PM and 5 PM.
If the Faculty is not satisfied with a student’s performance in the assignments, he/she will not be able to undertake this course.
The classes go on for six hours a week.
If you are absent for more than two sessions, will not be allowed to attend any more.