Data Science for Beginners- Data Science Intro Course

Data Science for Beginners: Data Science Intro Course, available at $44.99, has an average rating of 3.9, with 36 lectures, based on 68 reviews, and has 274 subscribers.

You will learn about Explanation of key concepts in data science: big data, data mining, libraries, datasets, APIs Programming languages and which ones to learn Data Science Methodology, expressed via Healthcare Insurance Company Case Study Experience The Power of Machine Learning and Natural Language Processing via Chatbot Example GitHub; how to use it for collaboration and version control. This course is ideal for individuals who are Beginners to Data Science. or Individuals considering switching fields. or Individuals who want to get a general overview before focusing on specific Data Science topics. It is particularly useful for Beginners to Data Science. or Individuals considering switching fields. or Individuals who want to get a general overview before focusing on specific Data Science topics.

Enroll now: Data Science for Beginners: Data Science Intro Course

Summary

Title: Data Science for Beginners: Data Science Intro Course

Price: $44.99

Average Rating: 3.9

Number of Lectures: 36

Number of Published Lectures: 36

Number of Curriculum Items: 37

Number of Published Curriculum Objects: 37

Original Price: $174.99

Quality Status: approved

Status: Live

What You Will Learn

Explanation of key concepts in data science: big data, data mining, libraries, datasets, APIs

Programming languages and which ones to learn

Data Science Methodology, expressed via Healthcare Insurance Company Case Study

Experience The Power of Machine Learning and Natural Language Processing via Chatbot Example

GitHub; how to use it for collaboration and version control.

Who Should Attend

Beginners to Data Science.

Individuals considering switching fields.

Individuals who want to get a general overview before focusing on specific Data Science topics.

Target Audiences

Beginners to Data Science.

Individuals considering switching fields.

Individuals who want to get a general overview before focusing on specific Data Science topics.

Welcome! If you see Data Science as a potential career in your future, this is the perfect course to get started with.

Our course does not require any previous Data Science experience. The goal of ‘Data Science for Beginners’ is to get you acquainted with Data Science methodology, data science concepts, programming languages, give you a peek into how machine learning works, and finally show you a data science tool like GitHub, which lets you collaborate with your colleagues.

Now, while this is a beginner course,  it does not mean that it is an easy course. For example in the Data Science methodology section, many different concepts are introduced. But please keep in mind that a. you will get concrete examples of what each concept means when it is brought up b. you can ask questions in the Q and A and c.most importantly, you are not meant to understand all the concepts.  Going through the methodology is meant to introduce you to concepts, not prepare you to fully apply them. You will get a chance to do this in other courses (ours or other providers).

Beyond this, you will get to build a simple chatbot.This hands-on activity will illustrate in a more interactive way how machine learning works and how you can provide a machine learning service such as this in your future career.

So, don’t hesitate. Start your Data Science learning journey today!

Course Curriculum

Chapter 1: Introduction to Data Science Concepts

Lecture 1: Matching Activity: Match Project and Data Role

Lecture 2: Intro to Data Science

Lecture 3: What a Data Scientist Does?

Lecture 4: Big Data

Lecture 5: Data Mining

Lecture 6: Machine Learning vs. Deep Learning

Lecture 7: Advice to Data Scientists

Chapter 2: Programming Languages

Lecture 1: Intro to Programming Languages

Lecture 2: Python

Lecture 3: SAS

Lecture 4: R

Lecture 5: SQL

Chapter 3: Data Science Methodology

Lecture 1: Data Science Methodology/Process Intro

Lecture 2: Business Understanding

Lecture 3: Data Understanding

Lecture 4: Data Prep

Lecture 5: Modeling

Lecture 6: Evaluation

Lecture 7: Deployment

Chapter 4: Data Science Via Chatbot

Lecture 1: Purpose of this Section

Lecture 2: What is a Chatbot?

Lecture 3: Signing up for Watson Assistant

Lecture 4: Creating a name – Healthcare Service Chatbot

Lecture 5: Intents

Lecture 6: Entities

Lecture 7: Suggestions for More Learning

Lecture 8: Section Recap: Natural Language Processing , Machine Learning, and Use Cases

Chapter 5: Libraries, APIs, Datasets

Lecture 1: Libraries

Lecture 2: APIs

Lecture 3: Datasets

Chapter 6: Github

Lecture 1: Intro to Github

Lecture 2: Create a Repository

Lecture 3: Creating Branch and Commit Changes

Lecture 4: Pull Request and Merging Pull Request

Chapter 7: Final Section and Survey

Lecture 1: Quick Survey (2 questions)

Lecture 2: Bonus Offer

Instructors

Ermin Dedic
All Things Data.

Rating Distribution

1 stars: 2 votes

2 stars: 3 votes

3 stars: 9 votes

4 stars: 29 votes

5 stars: 25 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!