The Full Stack Data Scientist Bootcamp®

[LeeAndro]

Published 6/2022MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHzLanguage: English | Size: 50.63 GB | Duration: 91h 0m

What You Get: Full Stats & Python| Full Machine Learning & Cloud Deployment| Deep Learning| Computer Vision & NLP

What you'll learn
Full Python For Data Science Course
Full Statistics For Data Science Course
Full Machine Learning Course
Full Cloud Deployment Course
Natural Language Processing(NLP)
Full Deep Learning Course
Computer Vision(CV)
Instructor Guide to Virtual Internship Projects
Learn Model Deployment on Web Service(AWS), Google Cloud(GCP), Microsoft Azure, Heroku, Flask API, Streamlit
Hands-On Exercises, Projects, Assignements
Requirements
This is a Bner to Advanced course and you do not need to have a prior knowledge or any prerequisites.​

The Instructor takes you right from the scratch till mastery.
Your laptop and internet connection is required
Your dedication to start and complete the course is highly recommended
Description
By far the most comprehensive, up-to-date, and credible Data Science course. The Full-Stack Data Scientist BootCamp is the ONLY course on Udemy that covers A to Z of lessons that will make you a Data Scientist.Created by Dr. Bright, a Ph.D. in Data Science holder, former Microsoft Senior Data Scientist, and a Visiting Faculty at Worcester Institute, this course covers everything that you need to know to become a Full Stack Data Scientist.The instructors and advisors of the course spent over 13 months creating and vetting the course to make sure it meets the industry and acad standards.With 100 hours of quality course curriculum, this course is the same as we use for our 18 months MS in Data Science program on campus and even more exciting are the Projects in the course to make you more efficient and confident in building Data Science and Artificial Intelligence (AI) products. The motivation is to bring Quality Data Science education to every serious learner at affordable cost. Everyone who cannot to spend $30,000 plus on attaining a data science degree at a top tier institute or anyone who cannot spend considerable amount of on campus away from their busy schedule.This course is meant for students and working professionals who wish to become Data scientists, Machine Learning Eeers, and AI professionals.Included in this course are:Full SQL Course from A-ZFull Python Course from A-ZFull Statistics for Data Science course from A-ZFull Machine Learning course from A-ZFull ML Model Cloud Deployment course A-ZFull Deep Learning course from A-ZFull Artificial Intelligence course from A-ZFull Computer Vision course from A-ZFull Natural Language Processing course from A-ZFull Microsoft Power BI course from A-ZReading Scientific Research Papehub for Data ScienceThe instructors and research assistants who created this course have done thorough research in developing this course and making sure to break the concepts down for your understanding taking into consideration people with different backgrounds and experience levels to enroll in this course.We understand the diversity of the audience that will enroll in this course, some with experience in the field and some completely new to the field, we understand that and we kept that in mind while creating the course. So don't worry, you are covered.The very instructors who created the course are going to be your MENTORS throughout the course so you will have someone to come to your aid whenever you get stuck or need help or any form of guidance.If you are interested in becoming a Full Stack Data Scientist, then this course is the right spot for you, and the ALL-in-ONE course to get you there.

Overview

Section 1: Data Science Overview

Lecture 1 Part 1: Data Science Overview

Lecture 2 What Is Data Science

Lecture 3 DA vs DS vs AI vs ML

Lecture 4 Industries That Use and Hire Data Scientist

Lecture 5 Applications of Data Science

Lecture 6 Data Science Lifecycle and the Maturity Framework

Lecture 7 Who is a Data Scientist

Lecture 8 Career Opportunities In Data Science

Lecture 9 Typical Backgrounds of Data Scientists

Lecture 10 The Ultimate Path To become a Data Scientist(Skills you need to develop)

Lecture 11 Typical Salary of a Data Scientist

Section 2: FULL SQL FOR DATA SCIENCE COURSE

Lecture 12 Overview

Section 3: SQL BNER LEVEL

Lecture 13 Introduction To SQL for Data Science

Lecture 14 Types of Databases

Lecture 15 What is a Query

Lecture 16 What is SQL

Lecture 17 SQL or SEQUEL

Lecture 18 SQL Installation

Lecture 19 SQL Installation Guide For MacOS

Lecture 20 SQL Installation Guide For Windows

Lecture 21 Extra Help in Installing SQL

Lecture 22 Overview of SQL workbench

Section 4: SQL Commands

Lecture 23 Introduction To SQL Commands

Lecture 24 SQL CRUD Commands

Section 5: Understanding and Creating SQL Databases

Lecture 25 SQL Schema

Lecture 26 Inserting Comments in SQL

Lecture 27 Creating Databases

Section 6: Understanding and Creating SQL Tables

Lecture 28 Overview of SQL Table

Section 7: Types Of SQL KEYS

Lecture 29 Primary Key

Lecture 30 For Key

Lecture 31 Composite Key

Lecture 32 Super Key

Lecture 33 Alternate Key

Section 8: Data Types In SQL

Lecture 34 SQL Data Types

Section 9: CREATE Table and INSERT Data into Table

Lecture 35 CREATE Table

Lecture 36 INSERT Data

Section 10: SQL Exercise & Solution

Lecture 37 Exercise 1 and solution

Section 11: SQL Constraints

Lecture 38 Understanding SQL Constraints

Lecture 39 NOT NULL & UNIQUE Constraints

Lecture 40 DEFAULT Constraints

Lecture 41 PRIMAY KEY Constraint

Lecture 42 Alter SQL Constraint

Lecture 43 Adding and Dropping SQL Constraint

Lecture 44 For Key Constraint

Section 12: SQL INTERMEDIATE LEVEL

Lecture 45 Creating Exiting Databases

Lecture 46 Overview Of Existing Databases

Lecture 47 The SELECT Statement in Details

Lecture 48 The ORDER BY Clause

Lecture 49 The WHERE Clause

Lecture 50 Operation with SELECT statement

Lecture 51 Aliasing in SQL

Lecture 52 The DISTINCT Keyword

Lecture 53 WHERE Clause with SQL Comparison operators

Lecture 54 Exercise 2 and Solution

Lecture 55 The AND, OR and NOT Operators

Lecture 56 Exercise 3 and Solution

Lecture 57 The IN Operator

Lecture 58 Exercise 4 and Solution

Lecture 59 The BETWEEN Operator

Lecture 60 Exercise 5 and Solution

Lecture 61 The LIKE Operator

Lecture 62 Exercise 6 and Solution

Lecture 63 The REGEXP Operator

Lecture 64 Exercise 7 and Solution

Lecture 65 IS NULL & IS NOT NULL Operator

Lecture 66 Exercise 8 and Solution

Lecture 67 The ORDER BY Clause in Details

Section 127: LSTM

Lecture 633 Lecture resources

Lecture 634 LSTM: An Introduction

Lecture 635 The LSTM Architecture

Lecture 636 LAB SESSION 1: LSTM

Lecture 637 LAB SESSION 2: Tween Sennt Analysis using RNN

Lecture 638 LAB SESSION 3: Tween Sennt Analysis using LSTM

Section 128: Sequence To Sequence Models (Seq2Seq)

Lecture 639 Sequence To Sequence models: An introduction

Lecture 640 Encoder & Decoder

Lecture 641 LAB SESSION: Language Translation

Lecture 642 LAB SESSION 2: Language Translation

Section 129: NLP PROJECT: Sennt Analyzer

Lecture 643 Project files

Lecture 644 Building Sennt Analyzer App

Lecture 645 LAB: Building Sennt Analyzer App

Section 130: Name Entity Recognition (NER)

Lecture 646 Lecture Resources

Lecture 647 NER : An Introduction

Lecture 648 Example of Name Entity Recognition

Lecture 649 How Name Entity Recognition works

Lecture 650 Applications of NER

Lecture 651 LAB SESSION: Hands-On Name Entity Recognition

Lecture 652 LAB SESSION 2: Name Entity Recognition

Lecture 653 LAB SESSION: Visualizing Name Entity Recognition

Lecture 654 Assignment

Section 131: NLP PROJECT: Building a Name Entity Recognition App

Lecture 655 Project: Building a Name Entity Recognition Web App

Lecture 656 Project: Building your NER web App

Section 132: NLP PROJECT: AI Resume Analyzer App

Lecture 657 NLP Project: Building AI Resume Analyzer

Lecture 658 Project: AI Resume Analyzer

This course is for bners who want to start a career in Data Science,Anyone who is interested to become a Full Stack Data Scientist,Any student who want to enter the field of Data Science after college,Any graduate who finds it difficult to find job in other IT field and will like to upskill in Data Science to secure a job,Any employee or worker looking for a career change,Anyone interested in the field of Artificial Intelligence,Anyone interested in the field of Computer Vision,Anyone interested in the field of Natural Language Processing,Anyone enrolled in other course and finding it difficult to understand the concepts,Anyone who wants to really dive deep into understanding the concepts and master it,Anyone who wants to secure a job in the field of Data Science, AI and Machine Learning,Anyone interested in building AI and Data Science products

HomePage:

Https://anonymz.com/https://www.udemy.com/course/the-full-stack-data-scientist-bootcamp/

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