About the Course
Python is one of the most used programming language across industries.
Modern Day IT industries have very high demands for the Engineers/Professionals having strong skills in Machine Learning with Python programming
A good hands-on knowledge of Machine Learning with Python programming skills is the building block for learning advanced topics like Artificial Neural Networks, Deep Learning etc.
Modern Day IT industries have very high demands for the Engineers/Professionals having strong skills in Machine Learning with Python programming
A good hands-on knowledge of Machine Learning with Python programming skills is the building block for learning advanced topics like Artificial Neural Networks, Deep Learning etc.
Week 1
Basics of Python Language
Python objects with details of shell/numbers/variables etc.
Python for Data Analysis using libraries like Pandas, Numpyetc.
Python for Data Exploration using libraries like Matplotlib, Seabornetc.
Completely hands on based learning
Python for Data preprocessing, splitting Data into train & Test set, features scanning
Machine Learning Basics
Linear Regression for One and Multiple Variables
Ordinary Least Square, Dummy Variables, One Hot Encoding, Gradient descent, Cost Function
Regression Trees
Evaluating Model Performance
Machine Learning Basics
Logistic Regression and Classification
Regularization (Ridge & Lasso)
ompletely hands on based learning
Python objects with details of shell/numbers/variables etc.
Python for Data Analysis using libraries like Pandas, Numpyetc.
Python for Data Exploration using libraries like Matplotlib, Seabornetc.
Completely hands on based learning
Week 2
Python for Data preprocessing, splitting Data into train & Test set, features scanning
Machine Learning Basics
Linear Regression for One and Multiple Variables
Ordinary Least Square, Dummy Variables, One Hot Encoding, Gradient descent, Cost Function
Regression Trees
Week 3
Evaluating Model Performance
Machine Learning Basics
Logistic Regression and Classification
Regularization (Ridge & Lasso)
ompletely hands on based learning
Week 4
Bias Variance Trade –off
K-Nearest Neighbors
Support Vector Machines
Kernels :: Polynomial, RBF etc.
Classification Trees
Completely hands on based learning
Naive Bayes classifier
Random Forest
Ensemble Learning
Bagging and Boosting
Unsupervised Learning
Completely hands on based learning
K-Means Clustering
Hierarchical Clustering
DBSCAN
Principal Component Analysis (PCA)
Completely hands on based learning
K-Nearest Neighbors
Support Vector Machines
Kernels :: Polynomial, RBF etc.
Classification Trees
Completely hands on based learning
Week 5
Naive Bayes classifier
Random Forest
Ensemble Learning
Bagging and Boosting
Unsupervised Learning
Completely hands on based learning
Week 6
K-Means Clustering
Hierarchical Clustering
DBSCAN
Principal Component Analysis (PCA)
Completely hands on based learning
Benefits and Post Program Deliverables
A digital toolkit of PPTs/software packages and study material for all participants
Opportunity to continue a yearlong internship from home
Interact with the experienced Industry training expert to work on real-life challenges
Complete Recording of the Classes on a daily basis
An opportunity to exchange ideas and thoughts with students participating from colleges PAN India IIT’s, NIT’s, and Reputed Universities
Small batches for one to one interaction and individual doubt sessions
Live demonstration of topics and practicals is included to ensure that the candidate can get hands-on exposure
Opportunity to continue a yearlong internship from home
Interact with the experienced Industry training expert to work on real-life challenges
Complete Recording of the Classes on a daily basis
An opportunity to exchange ideas and thoughts with students participating from colleges PAN India IIT’s, NIT’s, and Reputed Universities
Small batches for one to one interaction and individual doubt sessions
Live demonstration of topics and practicals is included to ensure that the candidate can get hands-on exposure
PREREQUISITES AND ELIGIBILITY
No coding experience required. We’ll start from scratch.
This course can be taken up by any undergraduate/postgraduate student of Basic & Applied Sciences, Engineering, and Computer Applications and also by Research Scholars/Faculties/Working Professionals who want to upskill themselves
Participants need to have a laptop/PC (with a minimum of 4 GB RAM, 100 GB HDD, Intel i3processor) and proper internet/Wi-Fi connection.
This course can be taken up by any undergraduate/postgraduate student of Basic & Applied Sciences, Engineering, and Computer Applications and also by Research Scholars/Faculties/Working Professionals who want to upskill themselves
Participants need to have a laptop/PC (with a minimum of 4 GB RAM, 100 GB HDD, Intel i3processor) and proper internet/Wi-Fi connection.
Rewards
Dr Subrat Kotoky
Email ID: rbpl.edu@gmail.com
Helpline: +91-Mobile no. 9085317465/8473874389 (And then press 2)+91-7409146082
Expert Profile
