What you'll learn
Build Robust Industry Machine Learning Models
Don't just learn, Become a Data Scientist through hands-on practice
Learn practical SQL skills needed by current industry
Understand the field of Data Science through demonstrable experience.
Learn from an industry expert

Requirements
This is a beginner course and the instructor with many years of experience in the industry and classroom breaks the concepts down for anyone at any level to understand. A laptop, internet connections and willingness to learn is enough to succeed in this comprehensive course.

Description
Data Science is bringing innovations to the world. The recent incident of Covid and ChatGPT is making the demand for Data scientists even more crucial in organizations.Employees with data science and analytical skills are highly valued and paid for in organizations. If you are interested in learning and understanding the field of data science, then this course is for you.In this course, you will get to understand the core areas of Data Science and the various career opportunities in Data Science. After that, you will start with SQL for Data Science to give you solid grounds for your data science career.This should give you the foundation needed for advanced concepts in data science such as Machine learning, Deep learning, Computer vision (CV), and Natural Language Processing (NLP). The instructor for this course has 15 years of industry experience as well as classroom experience in developing and deploying machine learning models in production. He is also instructor of top online courses and books. He combines his industry and academic experience in delivering the lessons. The lessons are broken down for easy understanding. A step by step approach is followed in order to cater for diverse audience such as beginners, intermediate as well as advanced learners.You only need your laptop, internet and willingness to learn and you are good to go.See you in the course.

Overview
Section 1: Introduction

Lecture 1 Overview

Lecture 2 The Big Picture

Lecture 3 Data Science Overview

Lecture 4 What is Data Science?

Lecture 5 DA vs DS vs AI vs ML

Lecture 6 Industries That Use and Hire Data Scientist

Lecture 7 Applications of Data Science

Lecture 8 Data Science Lifecycle and the Maturity Framework

Lecture 9 Who is a Data Scientist?

Lecture 10 Career Opportunities In Data Science

Lecture 11 Typical Backgrounds of Data Scientists

Lecture 12 The Ultimate Path To become a Data Scientist(Skills you need to develop)

Lecture 13 Typical Salary of a Data Scientist

Section 2: COMPLETE SQL FOR DATA SCIENCE COURSE

Lecture 14 Lecture resources

Lecture 15 All SQL Course Materials

Section 3: SQL : BEGINNER LEVEL

Lecture 16 Introduction To SQL for Data Science

Lecture 17 Types of Databases

Lecture 18 What is a Query?

Lecture 19 What is SQL?

Lecture 20 SQL or SEQUEL?

Lecture 21 SQL Installation

Lecture 22 SQL Installation Guide For MacOS

Lecture 23 SQL Installation Guide For Windows

Lecture 24 Extra Help in Installing SQL

Lecture 25 Overview of SQL workbench

Section 4: SQL COMMANDS

Lecture 26 Introduction To SQL Commands

Lecture 27 SQL CRUD Commands

Section 5: UNDERSTANDING AND CREATING SQL DATABASES

Lecture 28 SQL Schema

Lecture 29 Inserting Comments in SQL

Lecture 30 Creating Databases

Section 6: UNDERSTANDING AND CREATING SQL TABLES

Lecture 31 Overview of SQL Table

Section 7: TYPES OF SQL KEYS

Lecture 32 Keys in SQL

Lecture 33 Primary Key

Lecture 34 Foreign Key

Lecture 35 Composite Key

Lecture 36 Super Key

Lecture 37 Alternate Key

Section 8: DATA TYPES IN SQL

Lecture 38 SQL Data Types

Section 9: CREATE TABLE AND INSERT DATA INTO TABLE

Lecture 39 CREATE Table

Lecture 40 INSERT Data

Section 10: SQL CONSTRAINTS

Lecture 41 Understanding SQL Constraints

Lecture 42 NOT NULL & UNIQUE Constraints

Lecture 43 DEFAULT Constraints

Lecture 44 PRIMAY KEY Constraint

Lecture 45 Alter SQL Constraint

Lecture 46 Adding and Dropping SQL Constraint

Lecture 47 Foreign Key Constraint

Students who wish to work as Data Scientist,Working professionals who want to transition to the field of Artificial Intelligence(A.I.) , Machine Learning, Deep learning, Computer Vision(CV), Natural Language Processing(NLP),Anyone interested in building A.I applications such as ChatGPT or BARD,Anyone interesting in diving deeper into the field of Computer Vision(CV), Natural Language Processing(NLP),Anyone aspiring to be a Computer Vision(CV) or Natural Language Processing(NLP) engineer.,Anyone finding it difficult to understand the field and concepts in Data Science and wants a breakdown step-by-step guide in understanding these concepts.,Anyone who wants to be career secured and not easily affected by layoffs in organizations,Anyone looking for salary hikes and increase in salary with a lucrative tech career.

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