Post Graduate Program in Data Science and Machine Learning
4.5 /5- Offered bySkill Lync
Post Graduate Program in Data Science and Machine Learning at Skill Lync Overview
Duration | 32 weeks |
Total fee | ₹2.75 Lakh |
Mode of learning | Online |
Official Website | Go to Website  |
Credential | Certificate |
Post Graduate Program in Data Science and Machine Learning at Skill Lync Highlights
- Earn a certificate after completion of the course
- Career Service Assurance with access to Skill-Lync’s 500+
- Personalized Career Services Mentorship
- Easy EMI payment option available
- 1 Year Access to Skill-Lync’s Learning Management System (LMS)
Post Graduate Program in Data Science and Machine Learning at Skill Lync Course details
A software programmer or a developer who wants to venture into Data Science can easily apply for this course.
This course is suitable for a python developer who is just starting out and wants to pursue a career in Data Science.
Someone who wish to transition in their career from non-technical to technical field.
Understanding the Mathematics behind different Machine Learning Algorithms
Exploring SQL from basics to advanced level to utilize its powers for the Data Science domain
Understanding Machine Learning and its implementation in Python
Hands-on experience in Python Programming
Understanding Advanced Machine Learning Algorithms and Implementation of Tensorflow
The Post Graduate Program in Data Science and Machine Learning is the go-to course for students to understand Deep Learning, Artificial Intelligence, SQL, and Python Programming
With the help of mathematics and statistics, you will learn to identify and create a pattern from pieces of data
Blocks of data are made available through Data Science, and this Machine Learning crash course helps you test and train your models
The data science course syllabus focuses on teaching you how to analyse and process gathered data
Post Graduate Program in Data Science and Machine Learning at Skill Lync Curriculum
Core and Advanced Python Programming
Introduction to Python, Python Basics
Strings, Decision Control Statements
Repetition Statements and Console Input-Output
Lists, Tuples, Sets, Dictionary
Statistics and Probability for Data Sciences
Introduction to Machine Learning
Set Theory
Probability
Statistics
Probability Distribution
Introduction to Machine Learning Algorithms and their Implementation in Python
Introduction to Data Science and Programming Languages (Tools) for Data Science
Basics of Programming
Basics of Programming
Essential Python Libraries
Introduction to Machine Learning Cross-Validation, Bias-Variance Tradeoff
Machine Learning Fundamentals In Depth
Basics of Probability and Statistics
Basics of Machine Learning (ML) & Artificial intelligence (AI)
Supervised Learning - Prediction
Supervised Learning - Classification
Advanced Deep Learning using Python
Artificial Neural Network (Feed Forward Neural Network)
Activation Functions in Neural Networks
Deep Learning
Evaluation of Models
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