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Data Science & Python: Data Science with Real Problems (2)

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Data Science & Python: Data Science with Real Problems (2), available at $19.99, has an average rating of 3.5, with 37 lectures, 13 quizzes, based on 4 reviews, and has 84 subscribers.

You will learn about Use Python for Data Science Learn to use Pandas for Data Analysis Broadcast Data Science Project to the World Share Projects on Kaggle One Step Closer to the Artificial Intelligence Journey Learn Data Science from Experienced Professional Software Developers This course is ideal for individuals who are Those who want to specialize in Data Science with Python or Those who want to start and continue their education or career in data science, machine learning or artificial intelligence or Those who know Python basics and want to master Python for Artificial Intelligece It is particularly useful for Those who want to specialize in Data Science with Python or Those who want to start and continue their education or career in data science, machine learning or artificial intelligence or Those who know Python basics and want to master Python for Artificial Intelligece.

Enroll now: Data Science & Python: Data Science with Real Problems (2)

Summary

Title: Data Science & Python: Data Science with Real Problems (2)

Price: $19.99

Average Rating: 3.5

Number of Lectures: 37

Number of Quizzes: 13

Number of Published Lectures: 37

Number of Published Quizzes: 13

Number of Curriculum Items: 50

Number of Published Curriculum Objects: 50

Number of Practice Tests: 1

Number of Published Practice Tests: 1

Original Price: $199.99

Quality Status: approved

Status: Live

What You Will Learn

  • Use Python for Data Science
  • Learn to use Pandas for Data Analysis
  • Broadcast Data Science Project to the World
  • Share Projects on Kaggle
  • One Step Closer to the Artificial Intelligence Journey
  • Learn Data Science from Experienced Professional Software Developers

Who Should Attend

  • Those who want to specialize in Data Science with Python
  • Those who want to start and continue their education or career in data science, machine learning or artificial intelligence
  • Those who know Python basics and want to master Python for Artificial Intelligece

Target Audiences

  • Those who want to specialize in Data Science with Python
  • Those who want to start and continue their education or career in data science, machine learning or artificial intelligence
  • Those who know Python basics and want to master Python for Artificial Intelligece

THIS COURSE IS THE SECOND PART OF 7-STEP ARTIFICIAL INTELLIGENCE JOURNEY.

  1. Python   

  2. Data Science

  3. Visualization Tools

  4. Machine Learning

  5. Deep Learning

  6. Statistical Learning

  7. Reinforcement Learning

We will learn the Data Sciencerequired to learn our ultimate goal, Artificial Intelligence algorithms.

DATA SCIENCE COURSE DESCRIPTION

  • Data Science Introduction

  • Kaggle and Data Science

  • Introduction to Python

  • Python Data Science Tool Box

  • Cleaning Data

  • Pandas Foundation

  • Manipulating Data Frames with Pandas

  • Titanic Project

  • 1 Practice Exam: Final Exams

  • 12 Quizzes

  • BONUS

WHY PYTHON?

  • According to 2020 IEEE research, Python is one of the most used and preferred programming languages worldwide.

  • Python is the first choice of newcomers to coding thanks to its easy learning.

  • Python is open source, supported by the world’s largest companies such as Facebook or Google.

  • When it comes to data science, machine learning or artificial intelligence, Python language comes to mind first. This causes Python to have a large worldwide audience.

  • In terms of professional career, Python is one of the languages with the most opportunities.

WHY DATA SCIENCE?

  • Helping people make faster and more effective decisions.

  • Demand and job opportunities for data scientists with the increase of data.

  • Start-up opportunities.

  • Decision making ability.

THE OPPORTUNITIES YOU WILL HAVE WITH THIS COURSE

  • Coding ability from scratch: We will code together.

  • Codes and Templates: You can download every Python template and code we have created in the course. Thanks to this code and template, you create the infrastructure for the applications and projects that you will make later.

  • Theory and Logic: We not only tell you how to write code, but also the logic and theory behind the code we write, and why we write such a code.

  • In-class support: We don’t just give you video lessons. We have created a professional Python Programmer team and community to support you. This means that you will get answers to your questions within 24 hours.

WHO WE ARE: DATAI TEAM ACADEMY

DATAI TEAM is a team of Python Programmers and Data Scientists.

Let’s register for the course and start the Object-Oriented Programming adventure with Python.

Course Curriculum

Chapter 1: Data Science Introduction

Lecture 1: Data Science Introduction

Chapter 2: Kaggle and Data Science

Lecture 1: Kaggle Description 1

Lecture 2: Kaggle Description 2

Lecture 3: What is Kaggle Notebook (Kernel) ?

Lecture 4: Kaggle Profile Page

Lecture 5: Being Successful in Kaggle

Chapter 3: Introduction to Python

Lecture 1: Data Science Notebook Introduction

Lecture 2: Import and First Look Data

Lecture 3: Matplotlib

Lecture 4: Dictionary, Pandas and Logic Control

Lecture 5: Loop Data Structures (while and for)

Lecture 6: Homework 1

Chapter 4: Python Data Science Tool Box

Lecture 1: User Defined Function and Scope

Lecture 2: Nested, Default, Flexible, Lambda, Anonymous Functions

Lecture 3: Iterators and List Comprehension

Chapter 5: Cleaning Data

Lecture 1: Diagnose Data for Cleaning

Lecture 2: Exploratory Data Analysis (EDA)

Lecture 3: Visual Exploratory Data Analysis

Lecture 4: Tidy and Pivoting Data

Lecture 5: Concatenating Data and Data Types

Lecture 6: Missing Data and Testing with Assert

Chapter 6: Pandas Foundation

Lecture 1: Review of Pandas, Building Data Frames from Scratch,Visual and Statistical EDA

Lecture 2: Indexing and Resampling Pandas Time Series

Chapter 7: Manipulating Data Frames with Pandas

Lecture 1: Indexing, Slicing, Filtering and Transforming Data Frames

Lecture 2: Index Objects, Hierarchical Indexing, Pivoting, Stacking-Unstacking and Melting

Chapter 8: Data Science Final Exam

Chapter 9: Titanic Project

Lecture 1: Titanic Project Introduction

Lecture 2: Overview and Load Data

Lecture 3: Variable Description

Lecture 4: Univariate Variable Analysis: Categorical Variables

Lecture 5: Univariate Variable Analysis: Numeric Variables

Lecture 6: Exploratory Data Analysis (EDA)

Lecture 7: Outlier Detection

Lecture 8: Missing Value

Lecture 9: Titanic Project Conclusion

Chapter 10: Data Science Conclusion

Lecture 1: Data Science Conclusion

Lecture 2: Data Science Additional Resources

Lecture 3: BONUS

Instructors

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  • 3 stars: 1 votes
  • 4 stars: 1 votes
  • 5 stars: 1 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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