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Description:

  • The complete course structure is designed in association with ESDS keeping Cloud Data Centre where Scale and Volume are at different level.
  • The course is skill development oriented which can help in getting job effectively.
  • The syllabus is designed by the industry experts.
  • All sessions will be delivered by the experienced industry experts who themselves practice the subject
  • The program is a combination of Training + Guided project work by industry experts. Students will undergo training via live sessions during weekdays in July followed weekend mentorship in August for the project work.
  • Students will receive a certification on completion of the program.

About ESDS:

ESDS is one of India’s leading Managed Data Center Service and Auto-Scalable Cloud Solution provider. ESDS has expertise in Managed Data Center Services, Managed Cloud Solutions, Virtualization and Disaster Recovery Hosting, which is backed with exuberant Technical Support that has helped ESDS build lifetime relationships with customers.

Course Features:

  • To understand nature of problem and apply machine learning algorithms to solve those problems.
  • To learn how to design and program python application.
  • Understand and learn the python programming language with various python syntax, statements, operators.
  • Understand the concepts of Classes and Objects, OOP Concepts, Constructors, Exception Handling, File input output operations.
  • Understand Python libraries for Machine Learning such as Numpy, scipy, Scikit-learn, Pandas, Matplotlib, Math.
  • Learn concepts of Regression and classification.
  • Learn the concepts of decision tree and KNN algorithm.
  • Understand the Clustering and its fundamental concepts. Also learn the concepts of Artificial Neural Network.
  • After completion of this course, students will have a base to work in Data Science field

Who can apply?

This course is eligible for undergraduate third and fourth year Engineering students (B.E.) Following branches will be eligible for this courses  –
1. BE – IT, computer, Computer Science Engineering.
2. BE – Electronics, Electronics and Telecommunication

In case of any queries regarding the program, please contact support@apprend.in

Course Curriculum

Introduction to Basic Python Programming IDE: PyCharm
Python Features, Basic Syntax, Data Types, Basic Operators 01:08:00
Decision Making, Loops (While, for, Nested), Comments 01:08:00
python-pass, continue statement, python operators, python Date & Time 01:08:00
Introduction to Advance Python Programming
Python-Strings, List, Tuples, Dictionary, Functions and Methods, Classes and Objects 01:03:00
OOP Concepts, Constructors, Exception Handling, File input output operations 01:03:00
Python libraries for Machine Learning – Numpy, scipy 01:03:00
Scikit-learn, Pandas, Matplotlib, Math 01:03:00
Regression
Linear Regression- Basic of Linear Regression, Ridge, Lasso, Elastic Net 01:00:00
Robust regression with random sample consensus, 01:00:00
Polynomial Regression and Isotonic regression 01:00:00
Logistic Regression- Basics of Logistics Regression, Types of Logistic Regression (Binary, Multinomial, Ordinal) 01:03:00
Classification- Naïve Bayes, Support Vector Machine 01:00:00
Decision Tree
Impurity Measures, Features Importance 02:07:00
Ensemble Learning, Random Forests, Ada boost, Voting Classifier 02:07:00
KNN
Working of KNN, Algorithm 05:28:00
Dimensionality Reduction
Principal Component Analysis(PCA), Non-Negative Matrix Factorization, Advantages 05:28:00
Clustering Fundamentals
Basics, K-means algorithm, DBSCANS 01:08:00
Spectral Clustering, Agglomerative Hierarchical clustering 01:08:00
Artificial Neural Network – Concept, Feed forward and Feedback ANNs, Error Back Propagation, Convolutional neural networks 01:08:00

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