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 | Weekends |
Course Overview
The Certificate Program in Machine Learning and AI with Python online course is a short-term accreditation programme that will last for six months. This course is curated by the prestigious Indian Institute of Technology, Bombay, to help students learn about the different aspects of Machine Learning and AI.
Moreover, the Certificate Program in Machine Learning and AI with Python accreditation trains the working professionals and students in neural networks, decision trees, algorithms, classification, regression, etc. to build and enhance their skills in the most popular programming language Python.
Furthermore, in the Certificate Program in Machine Learning and AI with Python online accreditation, you will have live online lessons during the weekend to use your time efficiently during the weekend and manage your job.
You need to be a graduate or a diploma holder with a minimum of one year of experience to pursue this programme. Also, you need to have a working knowledge of C++, or Java, or MATLAB. Besides, you need to be well acquainted with the concepts of linear algebra, statistics, and calculus to make the most out of this course.
The Highlights
- Six-months course
- Live online lessons
- Certification available
- Offered by IIT Bombay
- Practical course
- Skilled faculty
Programme Offerings
- Live online learning
- Short-term course
- Self-paced learning
- Certification
- Skilled faculty
Courses and Certificate Fees
| Certificate Availability | Certificate Providing Authority |
|---|---|
| yes | IIT Bombay |
- Interested applicants need to pay a sum of Rs. 1,25,000 plus GST to enroll in the Certificate Programme in Machine Learning and AI with Python.
- You can pay online. You have the option to pay in installments too.
Certificate Program in Machine Learning and AI with Python fee structure
| Course Name | Fee in INR |
| Certificate Programme in Machine Learning and AI with Python | Rs. 1,25,000 + GST |
Eligibility Criteria
To be eligible for the Certificate Program in Machine Learning and AI with Python certification, you need to be a graduate or a diploma holder with at least one year of experience. Also, you need to know C++ or Java, or MATLAB. Besides, you should be thorough with the concepts of linear algebra, calculus, and statistics.
What you will learn
In the Machine Learning and AI with Python online accreditation programme, you will learn the following:
- Python, NumPy, and Pandas
- Scikit and SciPy
- ML Algorithms
- Natural Language Processing
- Reinforcement Learning
- To form predictive models using neural networks and decision trees.
- To build DataFrames from scratch.
- To create text classification systems with NLP with linear classifiers and deep learning methods.
- To visualise data with Matplotlib.
- Various Optimisation techniques
- To build AI models.
Who it is for
The online Certificate Program in Machine Learning and AI with Python is a specialised course in machine learning and AI with python that is suitable for the following individuals:
- Working professionals
- Managers who are leading a team of software developers
- Software developers
- People who are leading a machine learning-related project
- People who know programming languages like C++ or Java or MATLAB
- People who want to upskill
Admission Details
Step I: You can go through all the information on the Certificate Program in Machine Learning and AI with Python online certification here: https://iitb.emeritus.org/iitb-certificate-program-in-machine-learning-and-ai-with-python/thankyou.php.
Step II: After reading all the details, click on the ‘Apply Now’ button to proceed further.
Step III: Provide the necessary details, pay the fee, and start learning according to your batch commencement date.
The Syllabus
- Statistics
- Probability
- Linear Algebra
- Numerical Computing with Python (NumPy, Matplotlib)
- Introduction to Pandas for data import and export (Excel, CSV etc.)
- Basic Introduction to Scikit learn
- Introduction to Machine Learning with applications to different domains
- Supervised Learning
- Unsupervised Learning
- Semi-Supervised Learning
- Reinforcement Learning
- Idea of hypothesis space
- Machine learning as hypothesis selection problem
- Finite and Infinite hypothesis space
- Complexity of the hypothesis space
- The Idea of training, testing, and validation
- Cross-Validation
- Introduction to the Linear Regression Analysis problem with examples
- Solving Linear Regression using Matrix Inversion and Gradient Descent Based Approaches
- The Idea of Regularisation
- Lasso, ridge, and elastic net regularization
- Bias-Variance trade-off
- Underfitting and Overfitting of models
- Idea of empirical risk minimization principle
- Idea of generalization
- Lazy and active learners
- K nearest neighbor classification
- Linear discriminant analysis
- Bayesian approaches for classi cation
- Naïve Bayes’ algorithm
- Gaussian Discriminant Analysis
- Parameter estimation using MLE, MAP, Idea of EM algorithm for GMM
- Tree based classification,
- Decision Tree,
- ID3 algorithm for designing decision trees,
- Decision Tree for regression, Regularization in Decision Tree, Random Forest
- Support Vector machines
- Margin Based classification
- SVM and linearly and nonlinearly separable cases
- Idea of Kernels
- Multi-class SVM
- Examples using LIBSVM
- Introduction to Neural Networks,
- Biological neuron model and extension to artificial neuron models
- McCulloch-Pitts model
- Multi-layer perceptron
- Back-propagation based training of neural networks
- Introduction to convolution networks
- Idea of different layers in CNN
- Discussions on different CNN models for image recognition (Alexnet, VGG, Resnet, Inception Net etc.)
- Examples in Tensorflow / Keras
- Linear and nonlinear programming,
- Gradient based optimization,
- Convex optimization
- Idea of data clustering and density estimation
- K-means
- Fuzzy C Means
- Mean-Shift
- DBSCAN clustering techniques
- Implementation of K-means in Python
- Machine Learning techniques in NLP
- Language modelling
- Supervised and Unsupervised feature selection
- PCA
- ICA
- Implementation of PCA in Python
- Introduction to RL,
- Example of RL models,
- Markov Decision Process,
- Policy and Value Iterations,
- Bellman Equation,
- Temporal Difference Learning,
- Q Learning,
- Introduction to deep RL
- ML in Finance: Prof. Piyush Pandey (SOM)
- ML in computer vision: Vinay Namboodiri (IITK)
- ML in speech and text processing: Preethi Jyoti (CSE)
Instructors
IIT Bombay Frequently Asked Questions (FAQ's)
The classes will be held during the weekend to save you time and provide you flexibility.
The Machine Learning and AI with Python by Eruditus are spread across six months.
Indian Institute of Technology, Bombay, has created the course with the help of Eruditus.
To enrol in the Machine Learning and AI with Python accreditation programme, you need to be a graduate or a diploma holder with a minimum of one year of experience.