Machine Learning 17th Sep Batch
This Internship training leverages Machine Learning and Python with Numpy, Panda, and more to work on real industry challenges.
This internship is focused on efficiency: never spend time on confusing, out of date, incomplete ways of learning. Get handson training on Machine Learning. This comprehensive and projectbased internship will introduce you to all of the modern skills of a Data Scientist and along the way, you will build many realworld projects to add to your portfolio and solve some real industry challenges. This training would cover the following topics:
 Statistics
 Python Programming
 Introduction to Machine Learning
 Numpy Library
 Pandas Library
 Matplotlib Library
 Sklearn Library
 Linear Regression
 Logistic Regression
 Decision Tree and Random Forest
 Ensemble Techniques
 Naves Bayes and Support vector machine
 Unsupervised Learning Algorithms
 Dimensionality reduction Algorithms
 Introduction to Deep learning
Who this internship is for:
 Anyone with zero experience (or beginner/junior) who wants to learn Machine Learning, Data Science, Python and has a passion for statistics and Mathematics.
 You’re looking for one single opportunity to get hands ON Machine learning training to catch up to speed with the modern techniques of the industry.
Internship Features
 Lectures 29
 Quizzes 19
 Duration 18 Hours
 Skill level Beginner
 Language English
 Students 1615
 Certificate Yes
 Assessments Yes

Training Week1
 Live Introductory Session Recording
 1) Introduction to Statistics
 Quiz 1: Introduction to Statistics
 2) Summary Statistics
 Quiz 2: Summary Statistics
 3) Probability
 Quiz 3: Probability
 4) Permutations & Combinations
 Quiz 4: Permutations & Combinations
 5) Discrete Probability Distributions
 6) Continuous Probability Distributions
 7) Inferential Statistics
 Quiz 7: Inferential Statistics
 8) Basics of Python Programming
 Quiz 8: Basic of Python Programming
 9) Advanced Python Programming
 Quiz 9: Advanced Python Programming
 10) Python Libraries: Numpy
 Quiz 10: Python Libraries: Numpy

Training Week2
 11) Python Libraries: Pandas
 Quiz 11: Python Libraries: Pandas
 12) Python Libraries: Matplotlib
 Quiz 12: Python Libraries: Matplotlib
 13) Introduction to Machine Learning
 Quiz 13: Introduction to Machine Learning
 14) Python Libraries: Sklearn
 Quiz 14: Python Libraries: Sklearn
 15) Linear Regression
 Quiz 15: Linear Regression
 16) Logistic Regression
 Quiz 16: Logistic Regression

Training Week3
 17) Decision tree and Random forest
 Quiz 17: Decision tree and Random forest
 18) Ensemble techniques
 Quiz 18: Ensemble techniques
 19) Navise Bayes and SVM
 Quiz 19: Navise Bayes and SVM
 20) Unsupervised learning
 Quiz 20: Unsupervised learning
 21) Key ML Algorithms – KNN
 Quiz 21: Key ML Algorithms – KNN
 22) Neural Network and Deep Learning

Internship Week1
Your Internship Project is divided in ten steps. Understand the problem well and then work your way through the steps.

Internship Week2
Follow the process of Project Submission to ensure ontime and correct submission