Data Science with Analogies, Algorithms and Solved Problems

Data Science with Analogies, Algorithms and Solved Problems, available at Free, has an average rating of 4, with 18 lectures, 3 quizzes, based on 313 reviews, and has 19111 subscribers.

You will learn about Truly understand what Algorithms, Big Data, Machine Learning, and Data Science is. To understand how these different domains are distinct and how they collaborate as well. To really understand where these concepts are used using real life analogies. To understand the different algorithms and their working. To learn how these algorithms are applied to solve various problems. This course is ideal for individuals who are People/Researchers interested in machine learning or Technologists who are curious about how deep learning really works or Any student willing to begin a career in machine learning or People who want to brush up their basics. It is particularly useful for People/Researchers interested in machine learning or Technologists who are curious about how deep learning really works or Any student willing to begin a career in machine learning or People who want to brush up their basics.

Enroll now: Data Science with Analogies, Algorithms and Solved Problems

Summary

Title: Data Science with Analogies, Algorithms and Solved Problems

Price: Free

Average Rating: 4

Number of Lectures: 18

Number of Quizzes: 3

Number of Published Lectures: 18

Number of Published Quizzes: 3

Number of Curriculum Items: 21

Number of Published Curriculum Objects: 21

Original Price: Free

Quality Status: approved

Status: Live

What You Will Learn

Truly understand what Algorithms, Big Data, Machine Learning, and Data Science is.
To understand how these different domains are distinct and how they collaborate as well.
To really understand where these concepts are used using real life analogies.
To understand the different algorithms and their working.
To learn how these algorithms are applied to solve various problems.

Who Should Attend

People/Researchers interested in machine learning
Technologists who are curious about how deep learning really works
Any student willing to begin a career in machine learning
People who want to brush up their basics.

Target Audiences

People/Researchers interested in machine learning
Technologists who are curious about how deep learning really works
Any student willing to begin a career in machine learning
People who want to brush up their basics.

Interested to know about the field of Machine Learning?

Then this course is for you! This course has been designed such that we can share our knowledge and help you learn complex theory, algorithms and coding libraries in a simple way.

We will walk you into the World of Machine Learning. With every tutorial you will develop new skills and improve your understanding of this field. While preparing this course special care is taken that the concepts are presented in fun and exciting way but at the same time, we dive deep into machine learning.

Here is a list of few of the topics we will be learning:

• Difference between Data Mining and Deep Learning

• Data and 5 Vs of Big Data

• Types of Attributes

• Outliers

• Supervised learning, Unsupervised learning, Reinforcement learning

• Python Libraries

• CNN, RNN, LSTM

• K – means Clustering Algorithm

• Bayesian Algorithm, ID3 Algorithm

• Simple Linear Regression

• Anaconda

• Visualization

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Lecture 2: Data Mining and Deep Learning

Lecture 3: Big Data

Lecture 4: Attributes

Lecture 5: Outlier

Lecture 6: Libraries in Python

Chapter 2: Types Of Machine Learning and Algorithms

Lecture 1: Supervised Learning

Lecture 2: Bayesian Classifier

Lecture 3: ID3 Algorithm

Lecture 4: Decision Tree

Lecture 5: Regression

Lecture 6: Unsupervised Learning

Lecture 7: K-means clustering

Lecture 8: Reinforcement Learning

Chapter 3: Fundamentals of Deep Learning

Lecture 1: CNN Algorithm

Lecture 2: RNN and LSTM Algorithm

Lecture 3: Data Visualization

Lecture 4: Anaconda Installation

Instructors

Ajay Dhruv, Ph.D.
Instructor at Udemy
Neha Mayekar
Software Engineer at Capgemini
Shreya Pattewar
Student at Vidyalankar Institute Of Technology
Shubham Patil
Pursuing IT Engineering from VIT Mumbai, India

Rating Distribution

1 stars: 8 votes
2 stars: 18 votes
3 stars: 68 votes
4 stars: 109 votes
5 stars: 110 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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