Get updates on Eligibility, Admission, Placements Fees Structure
Quick Facts
| Medium Of Instructions | Mode Of Learning | Mode Of Delivery |
|---|---|---|
| English | Self Study, Virtual Classroom, Campus Based/Physical Classroom | Video and Text Based |
Course Overview
Artificial intelligence and machine learning are two of the most popular emerging technologies globally. The Post Graduate Certificate Programme in AI and Machine Learning will introduce all the major AI and ML concepts. You will explore computational skills and skills to generate actionable insights. It will allow you to gain expertise in the domain. The programme has a duration of 12 months.
The AI and Machine Learning course has an experiential learning model. The course instructors will demonstrate the implementation of ML and AI concepts via hands-on tutorials. The course will have exercise-based sessions to help you implement your newly learned skills. These practices will help you recognize business insights that you can generate.
After completing the AI and Machine Learning training program, you will earn a certificate and IIM Alumni status from IIM Kashipur. Throughout the training, eminent faculty members of IIM Kashipur will guide you using an industry-relevant curriculum. Moreover, the course provides you with 30 hours of Tableau Masterclass for effective learning outcomes.
The Highlights
- IIM Alumni status by IIM Kashipur
- 12-month course duration
- Certificate from IIM Kashipur
- 30 hours of Tableau Masterclass by Nulearn
- Blended, experiential learning model
- Capstone project
- Hands-on tutorials
- Five-day campus visit to IIM Kashipur
- Industry-relevant syllabus
- Eminent faculty members from IIM Kashipur
- Online sessions
- Case studies and simulations
Programme Offerings
- IIM Alumni status
- 12-month course duration
- Certificate from IIM Kashipur
- 30 hours of Tableau Masterclass by Nulearn
- Experiential learning model
- Capstone Project
- Hands-on tutorials
- 5-day campus visit to IIM Kashipur
- Industry-relevant syllabus
Courses and Certificate Fees
| Certificate Availability | Certificate Providing Authority |
|---|---|
| yes | IIM Kashipur |
Post Graduate Certificate Programme in AI and Machine Learning fee structure
Course option | Fee |
For Indian resident students | Rs 1,70,000 |
For international students | $ 2800 |
Eligibility Criteria
To join the AI and Machine Learning course by Nulearn, you should hold a bachelor’s degree (any discipline) from a recognized university. Nulearn prefers candidates with Mathematics at the 10+2 level, but it is not mandatory. Also, one-year corporate work experience is desired but not necessary to apply.
What you will learn
By completing the PG Certificate Course in AI and Machine Learning, you will gain fluency in:
- Comprehending the skill to generate actionable insights from real-time data
- Understanding the foundations of artificial intelligence and concepts of machine learning
- The significance of data-driven decision-making in an organization
- Using Python and R for implementing ML concepts
Admission Details
- Find the Post Graduate Certificate Programme in AI and Machine Learning by clicking https://www.nulearn.in/courses/post-graduate-certificate-program-in-ai-machine-learning#Syllabus.
- Tap on “Apply Now” to reach the registration webpage.
- Log in or register on the website with your details.
- Tap on “Register” after filling in the particulars.
- Verify your email via the verification mail and then return to fill out the application form by paying the application fee.
- A panel of experts will review your application, and its result will be communicated to you through your registered email ID.
- Once you get shortlisted, you will get your LOI.
- Then, you can finish the admission procedure by paying the programme fee.
Application Details
The AI and Machine Learning certification program by Nulearn has an application form. You need to fill in your contact details and academic and professional information to proceed. You also have to upload your resume for the review process. When you get shortlisted by the selection committee, you will receive an LOI, and then, you can pay the course fee to start learning.
The Syllabus
Introduction to AI
- Introduction to AI
- Evolution of Artificial Intelligence
- Goals of Artificial Intelligence
Business Analytics and Machine Learning
- Overview of Business Analytics
- Foundations of Business Analytics and Data-Driven Decision Making
- Basics of Machine Learning
Introduction to R
- Introduction to R Programming
- Getting Started with R
- Loading and Handling Data in R
- Exploring Data in R
- Operators and Expressions
- Control Structures
- Loops
- Functions
- R Packages
Introduction to Python
- Basics of Python Programming
- Operators and Expressions
- Decision Statements
- Loop Control Statements
- Functions & Python Packages
- Working with Files
- Object Oriented Concepts
Probability and Random Variables
- Random Experiment, Rules of Probability
- Conditional Probability, Statistical Independence
- Joint Probability, Marginal Probability
- Random Variables, Expectation and Variance
- Probability Distribution of Discrete and Continuous Variables
Descriptive Analytics
- Measures of Central Tendency, Dispersion and Shape
- Correlation and Covariance
- Outliers and Missing Data
Inferential Analytics
- Sampling Methods
- Statistical Plots and Applications: Histogram, Bar Plot, Pie Chart, Box Plot, Density Plot, Scatter Plot etc.
- Creating Awesome Plots using R/Python
Data-Driven Decision-Making
- Problem-solving in Real/Simulated Business Conditions
Causal Inference
- A Brief History of Causal Inference
- Causal Machine Learning
- Directed Acyclic Graph (DAG)
Building Statistical Models
- The Art and Science of Statistical Modelling
- Statistical Modelling from a Business Perspective
Dimensionality Reduction Methods
- Principal Component Analysis
Regression Techniques
- Motivation for Linear Regression
- Ordinary Least Squares
- Inference
- Dummy Variables
- Functional Forms
- Advanced Techniques
- Linear Probability Model
Time Series and Forecasting Techniques
- Trends and Seasonality
- Stationarity
- Error Correction Models
- One-step-ahead Forecast
- Multiple-step-ahead Forecast
Classification Techniques
- Logistic Regression
- Decision Trees
- Support Vector Machines
Evaluation of Classification Models
- K-fold validation
- ROC and AUC Metric
- Confusion Matrix
Ensemble Techniques
- Random Forest
- Bagging
- Boosting
- Stochastic Gradient Boosting
Clustering Techniques
- K-means
- Hierarchical
- DBSCAN
Clustering Concepts
- Distance Types in Clustering
- Clustering Performance Measures
- Text Analytics Process & Applications
- Building Corpus
- Corpus Pre-Processing
- Sentiment Analysis
- Topic Modelling
- Text Clustering
- Introduction to Neural Networks
- Tensors & Tensor Operations
- TensorFlow & Keras
- Deep learning & Anatomy of Neural Networks
- Recurrent Neural Networks
Convolutional Neural Networks
- CNN overview
- Convolutional Layer
- Pooling Layer
- CNN Model Architecture
- Building CNN Model
Image Analytics
- Understanding Image
- Image Formation
- Image Segmentation
- Pattern Recognition in Image
- Image Pre-processing and Features Extraction
Computer Vision
- Basic Concepts
- Business Applications
- Learning and Inference in Vision
- Models for Computer Vision
- TensorFlow Recognition Application
- Challenges and Risks Associated with Implementing Computer Vision
Natural Language Processing
- Fundamentals of NLP
- Business Applications
- Building NLP System
- Capstone Project
- Capstone Project Review
- Capstone Project Presentations
- Synthesis
Introduction
- Introduction to Tableau
- Data Connection
- Tableau Environment
Basic Charts
- Text Tables
- Highlight Tables
- Pie Charts
- Bar Chart
- Stacked Bar Chart
- Side by Side Bar Chart
- Circle Chart
- Side by Side Circle Chart
- Bubble Chart
Advanced Charts - I
- Heat Map
- Tree Map
- Area Chart Discrete
- Area Chart Continuous
- Bullet Graph
- Symbol Map
- Filled Map
- Histogram & Bins
Advanced Charts - II
- Box and Whisker
- Line Chart Continuous
- Line Chart Discrete
- Dual Line Chart
- Dual Combination
- Scatter Plot
Customising Charts
- Percentage Of
- Totals
- Filters & Highlighters
- Groups
- Hierarchy
- Sets
- Parameters
- Calculated Fields
- Dashboard
- Storyboard
Instructors
IIM Kashipur Frequently Asked Questions (FAQ's)
Candidates will make use of Tableau and the R and Python software during this programme.
Yes, there is an exclusive corporate pricing plan. The available discount for corporate professionals ranges from five to ten percent depending on the number of nominations. You can write at connect@nulearn.in for any query.
No loan facility is available for international students of the PG Certificate Course in AI and Machine Learning.
As the course has a blended learning model, the programme houses a five-day campus visit at IIM Kashipur.