BASE PYTHON PROGRAMMING
Python Data Types, List,Strings, Dictionaries,Tuples,Functions,Sets, Program Control Flow, Modules, Simulation,Comprehension (Multiple and Nested)Extended Keyword Arguments (*args, **kwargs)Closures and Decorators, Generators and Iterators Protocol@staticmethod & @classmethod,Object Oriented Programming. Encapsulation, Operator Overloading. Python Packages and Modules etc
With Plenty of projects implementation
ADVANCED PYTHON PROGRAMMING
- We will cover Numpy, Pandas, Matplotlib, Seaborn,SciPy & Statmodels, Sklearn
- With Plenty of projects implementation
- Implementation of all statistical methods using Python Programming
- With Plenty of projects implementation
ADVANCED STATISTICS
Time Series Models & Applications,,ARIMA Model,Monte Carlo simulation, Generalized linear models, Bayesian Network Analysis, Markov Process, Stochastic Process,Bootstrapping,Hidden Markov Chains,Couplas,Extreme Value Theory, Multivariate Calculus etc.
With Plenty of projects implementation
DATA ANALYSIS
Fundamentals of Mathematical Statistics & Probability, Descriptive Statistics, Discrete & Continuous Random Variables, Transformations, Distributions, Normal Distribution, Moment Generating Functions, Central limit theorem, Statistical Inference, Estimation Methods, Maximum Likelihood Estimation, Confidence Intervals, Hypotheses Test, Correlation, Regression Analysis, ANOVA, Credibility Theory, Bayesian Networks, Mortality Estimation etc.
Implemented using R/Python Programming
MACHINE LEARNING
Supervised Learning, Unsupervised Learning. Linear Regression, Logistic Regression, K nearest neighbors and Decision Trees, Support Vector machine, Random Forest, and Naive Bayes. Dimensionality Reduction, k-means Clustering, Hidden Markov Model, DBSCAN Clustering, Principal Component Analysis, Singular Value
Decomposition, Association Rule
Model Deployment in clouds.
With Plenty of projects implementation-TOOLS-SKLEARN,STATMODELS
DEEP LEARNING
The perceptron, Neural network learning, Back-Propagation, Autoencoders, Batch-normalization Overfitting & generalization Intro to CNNs, Convolution, Correlation, Filtering, CNN architectures, Detection, Segmentation, Visualizing & understanding, Advanced CNNs for computer vision, Recurrent Neural networks (RNNs),Advanced RNN,LSTM, GRU, Generative Adversarial Networks (GANs)
With Plenty of projects implementation-TOOLS-TENSORFLOW & PYTORCH
ARTIFICIAL INTELLIGENCE
Deep Learning,NLP,Fuzzy Logic, Image Classification, Computer Vision ,Logic Programming. Heuristic Search Techniques & Creating Intelligent Agents with Reinforcement Learning.
Announcement
The admissions for the current session has been opened for summer programs 2024.Free online counselling sessions are in progress for each participant. Please click here to take an appointment to choose the right career and further information.