CERTIFICATION IN ARTIFICIAL INTELLIGENCE & MACHINE LEARNING

CERTIFICATION IN ARTIFICIAL INTELLIGENCE & MACHINE LEARNING

COURSE DESCRIPTION (Course Type - Certificate)

This Certificate Program In Artificial Intelligence & Machine Learning Has Been Developed By Industry Experts To Help You Learn The Applications Of AI And ML From Scratch And Build Powerful Models To Generate Useful Business Insights And Predictions. It Has Been Designed For Fresh Graduates And Working Professionals Looking To Build Their Career In Data Science & ML.

[Note: The Program Comes In Two Formats: Weekday Format For Fresh Graduates And Weekend Format For Working Professionals.]

COURSE LEARNING

Upon Completion Of This Course, You Will Be Able To:

MODULE 1 - PYTHON PROGRAMMING

Introduction To Programming And Python Data Types | Operators |Expressions | Conditionals | Loops | Functions | Recursion | OOPS Concepts Data Structures | Numpy | Pandas | Error Handling | Scikit-Learn Library

MODULE 2 - SUPERVISED LEARNING AND DISCRIMINATIVE MODELS

Introduction To Supervised Learning And Performance Analysis | Logistics Regression | K-NN | Data Balancing Techniques And Applications | Classification And Regression Trees | Decision Trees And Random Forest | Support Vector Machines (SVM)

MODULE 3 - UNSUPERVISED LEARNING, GENERATIVE MODELS AND PATTERN DISCOVERY

Introduction To Unsupervised Learning Clustering | K-Means Clustering | Hierarchical Agglomerative Clustering And DBSCAN

MODULE 4 - DEEP LEARNING

Introduction To Deep Neural Network

Convolutional Neural Network | Implementation Of Convolutional Neural Network (ConvNet/CNN) | Architectures ConvNet/CNN And Demonstration

MODULE 5 - NATURAL LANGUAGE PROCESSING & NLTK

What Is NLP? | Typical NLP Tasks | Sentence Segmentation & Tokenization | Stemming, Lemmatization | Part Of Speech – POS | Named Entity Recognition (NER) | Parsing, Chunking | Stop Words Removal (English) | Corpora/Corpus | Context Window – Bi-Gram, N-Gram | Applications Of NLP | Introduction To The NLTK Library | Processing Raw Text | Regular Expression | Normalizing Text | Processing Raw Text – Tokenize Sentences | String Processing With Regular Expression | Normalizing Text | Extracting Features From Text | Bag-Of-Words(BoW), TF-IDF | Naïve Bayes Classifier

Course Project

• TEXT CLASSIFICATION
• IMAGE CLASSIFICATION
• HOUSE PRICE PREDICTION

Course Duration And Learning Pattern

Duration Of Certificate – 6 Week

Classes’ Distribution – 50% Theory Classes And 50% Implementation

Key Highlights

• Assignments Students Will Receive Timely Assignment Related With Course Topics.
• Discussions Apart From Classes You Will Get An Extra Session For Topic Discussion.
• Quizzes Topic Quizzes For Learning With Fun.
• Group Requirements/Group Projects Apart From Session Project You Can Work On Group Projects Also.
• Attendance Policy 85%
• Instructor Feedback One Can Directly Report About The Feedback Of Instructor.