INTRODUCTION:

This course is designed for professionals who want to explore data incepting from cleaned data set to Statistical Analysis and recommend most optimized solution. This course helps to processes and methods to extract expertise from data in several forms, sometimes structured or unstructured,which is a continuation of a number of a data analysis system. Data science implements tactics and hypotheses drawn from many fields in the broad areas of computer science and information science, signal processing,machine learning and Pattern recognition, predictive analytics, visualization,uncertainty modeling,data compression,computer programming,data warehousing,high performance computing and artificial intelligence

COURSE HIGHLIGHTS:

Learn Regression: Simple Linear Regression, Multiple Linear Regression, Polynomial Regression, SVR, Decision Tree Regression and Random Forest Regression

Learn Classification: Logistic Regression, K-NN, SVM, Kernel SVM, Naive Bayes, Decision Tree Classification and Random Forest Classification

Learn Clustering: K-Means and Hierarchical Clustering

Learn Association Rule Learning: Apriori Algorithm and Eclat

Learn Reinforcement Learning: Upper Confidence Bound, Thompson Sampling

Learn Natural Language Processing: Bag-of-words model and algorithms for NLP

Learn Deep Learning: Artificial Neural Networks, Convolutional Neural Networks

Learn Dimensionality Reduction: PCA, LDA, Kernel PCA

Learn Model Selection & Boosting: k-fold Cross Validation, Parameter Tuning, Grid Search, XGBoost

Moreover, the course is packed with practical exercises which are based on real-life examples. So not only will you learn the theory, but you will also get some hands-on practice building your own models.

This course also includes both Python and R code templates which you can download and use on your own projects.

WHO SHOULD ATTEND

Anyone interested in Machine Learning. Students who have at least high school knowledge in math and who want to start learning Machine Learning.

Any people who are not that comfortable with coding but who are interested in Machine Learning and want to apply it easily on datasets.

Any students in college who want to start a career in Data Science.

Any data analysts who want to level up in Machine Learning.

Any people who want to create added value to their business by using powerful Machine Learning tools.

contact details

R.Dinesh babu

rrrdinesh88@gmail.com

+91 9626201705

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About the Trainer

4.8 Avg Rating

224 Reviews

1703 Students

23 Courses

Dinesh Babu R

B.TECH, MBA,PH.D

15 Years of Experience

I have Completed B.Tech and MBA from ICFAI Business School (IBS), Hyderabad and completed Ph.D. in the field of Data Analytics in University of Madras. I am working for Capgemini as Senior Data Analyst, also worked for iGate Global solution as Consultant in Analytics division. As a part-time, am providing Machine Learning using Python, Data Science using R, Data Analysis, and Advanced Statistics Training to Indian and overseas students over past 8 years. I am CBAP certified professional.
As teaching pedagogy, approach is a case study oriented, wherein every session will have a case study assignment that the participant has to implement practically. Beyond theoretical knowledge, learning methodology heavily focus on use of examples, case studies and project work leads to acquire in-depth exposure in every facet of syllabus. I will share the entire training material along with the licenced material of CBAP certification. The class is more of Practical oriented session and interactive. Also, I will share the live project along with the training session. So, that participant won't have any skill gap after attended the training program.