This Certificate Program in Data Science & Machine Learning has been developed by industry experts to help you learn the applications of Data Science 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.
CERTIFICATION IN Data Science & MACHINE LEARNING
[Note: The program comes in two formats: weekday format for fresh graduates and weekend format for working professionals.]
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 – Data Analysis
Introduction to EDA | Deal with missing data |Data Cleaning | Data visualization
MODULE 3 - SUPERVISED LEARNING
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 4 - UNSUPERVISED LEARNING
Introduction to Unsupervised Learning Clustering | K-Means Clustering | Hierarchical Agglomerative Clustering and DBSCAN
MODULE 5 - DEEP LEARNING
Introduction to Deep Neural Network
Convolutional Neural Network | Implementation of Convolutional Neural Network (ConvNet/CNN) | Architectures ConvNet/CNN and Demonstration
· IMAGE CLASSIFICATION
· HOUSE PRICE PREDICTION
Course Duration and Learning pattern
Duration of Certificate – 4 Week
Classes’ distribution – 50% Theory Classes and 50% Implementation
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.