Mô tả

Are you ready to start your path to becoming a Data Scientist! 

This comprehensive course will be your guide to learning how to use the power of Python to analyze data, create beautiful visualizations, and use powerful machine learning algorithms!

Data Scientist has been ranked the number one job on Glassdoor and the average salary of a data scientist is over $120,000 in the United States according to Indeed! Data Science is a rewarding career that allows you to solve some of the world's most interesting problems!

This course is designed for both beginners with some programming experience or experienced developers looking to make the jump to Data Science!

This comprehensive course is comparable to other Data Science bootcamps that usually cost thousands of dollars, but now you can learn all that information at a fraction of the cost! With over 100 HD video lectures and detailed code notebooks for every lecture this is one of the most comprehensive course for data science and machine learning on Udemy!

We'll teach you how to program with Python, how to create amazing data visualizations, and how to use Machine Learning with Python! Here a just a few of the topics we will be learning:

  • Programming with Python
  • NumPy with Python
  • Using pandas Data Frames to solve complex tasks
  • Use pandas to handle Excel Files
  • Web scraping with python
  • Connect Python to SQL
  • Use matplotlib and seaborn for data visualizations
  • Use plotly for interactive visualizations
  • Machine Learning with SciKit Learn, including:
  • Linear Regression
  • K Nearest Neighbors
  • K Means Clustering
  • Decision Trees
  • Random Forests
  • Natural Language Processing
  • Neural Nets and Deep Learning
  • Support Vector Machines
  • and much, much more!

Enroll in the course and become a data scientist today!


Bạn sẽ học được gì

Use Python for Data Science and Machine Learning

Use Spark for Big Data Analysis

Implement Machine Learning Algorithms

Learn to use NumPy for Numerical Data

Learn to use Pandas for Data Analysis

Learn to use Matplotlib for Python Plotting

Learn to use Seaborn for statistical plots

Use Plotly for interactive dynamic visualizations

Use SciKit-Learn for Machine Learning Tasks

K-Means Clustering

Logistic Regression

Linear Regression

Random Forest and Decision Trees

Natural Language Processing and Spam Filters

Neural Networks

Support Vector Machines

Yêu cầu

  • Some programming experience
  • Admin permissions to download files

Nội dung khoá học

27 sections

Course Introduction

3 lectures
Introduction to the Course
03:33
Course Help and Welcome
00:36
Course FAQs
03:02

Environment Set-Up

1 lectures
Python Environment Setup
11:14

Jupyter Overview

3 lectures
Updates to Notebook Zip
00:09
Jupyter Notebooks
13:48
Optional: Virtual Environments
09:51

Python Crash Course

8 lectures
Welcome to the Python Crash Course Section!
00:17
Introduction to Python Crash Course
01:26
Python Crash Course - Part 1
19:29
Python Crash Course - Part 2
15:14
Python Crash Course - Part 3
16:39
Python Crash Course - Part 4
15:37
Python Crash Course Exercises - Overview
03:35
Python Crash Course Exercises - Solutions
11:56

Python for Data Analysis - NumPy

8 lectures
Welcome to the NumPy Section!
00:10
Introduction to Numpy
02:12
Numpy Arrays
16:49
Quick Note on Array Indexing
00:48
Numpy Array Indexing
18:23
Numpy Operations
07:04
Numpy Exercises Overview
02:46
Numpy Exercises Solutions
15:31

Python for Data Analysis - Pandas

11 lectures
Welcome to the Pandas Section!
00:14
Introduction to Pandas
01:44
Series
10:39
DataFrames - Part 1
15:31
DataFrames - Part 2
17:10
DataFrames - Part 3
09:12
Missing Data
06:19
Groupby
06:48
Merging Joining and Concatenating
08:55
Operations
12:04
Data Input and Output
14:00

Python for Data Analysis - Pandas Exercises

5 lectures
Note on SF Salary Exercise
00:22
SF Salaries Exercise Overview
01:55
SF Salaries Solutions
15:25
Ecommerce Purchases Exercise Overview
02:11
Ecommerce Purchases Exercise Solutions
15:12

Python for Data Visualization - Matplotlib

7 lectures
Welcome to the Data Visualization Section!
00:22
Introduction to Matplotlib
03:02
Matplotlib Part 1
16:57
Matplotlib Part 2
15:51
Matplotlib Part 3
11:51
Matplotlib Exercises Overview
01:46
Matplotlib Exercises - Solutions
10:19

Python for Data Visualization - Seaborn

9 lectures
Introduction to Seaborn
02:58
Distribution Plots
18:20
Categorical Plots
17:17
Matrix Plots
10:14
Grids
08:30
Regression Plots
07:13
Style and Color
08:21
Seaborn Exercise Overview
01:53
Seaborn Exercise Solutions
07:08

Python for Data Visualization - Pandas Built-in Data Visualization

3 lectures
Pandas Built-in Data Visualization
13:27
Pandas Data Visualization Exercise
01:22
Pandas Data Visualization Exercise- Solutions
08:55

Python for Data Visualization - Plotly and Cufflinks

3 lectures
Introduction to Plotly and Cufflinks
03:22
READ ME FIRST BEFORE PLOTLY PLEASE!
00:53
Plotly and Cufflinks
18:38

Python for Data Visualization - Geographical Plotting

5 lectures
Introduction to Geographical Plotting
00:58
Choropleth Maps - Part 1 - USA
19:26
Choropleth Maps - Part 2 - World
06:53
Choropleth Exercises
03:11
Choropleth Exercises - Solutions
10:01

Data Capstone Project

9 lectures
Welcome to the Data Capstone Projects!
00:17
911 Calls Project Overview
02:07
911 Calls Solutions - Part 1
14:29
911 Calls Solutions - Part 2
17:37
Bank Data
00:11
Finance Data Project Overview
03:06
Finance Project - Solutions Part 1
16:13
Finance Project - Solutions Part 2
18:11
Finance Project - Solutions Part 3
06:23

Introduction to Machine Learning

6 lectures
Welcome to Machine Learning. Here are a few resources to get you started!
00:21
Welcome to the Machine Learning Section!
00:31
Supervised Learning Overview
08:21
Evaluating Performance - Classification Error Metrics
16:37
Evaluating Performance - Regression Error Metrics
05:36
Machine Learning with Python
09:27

Linear Regression

6 lectures
Linear Regression Theory
04:33
model_selection Updates for SciKit Learn 0.18
00:26
Linear Regression with Python - Part 1
18:16
Linear Regression with Python - Part 2
07:05
Linear Regression Project Overview
02:31
Linear Regression Project Solution
18:43

Cross Validation and Bias-Variance Trade-Off

1 lectures
Bias Variance Trade-Off
06:25

Logistic Regression

6 lectures
Logistic Regression Theory
11:53
Logistic Regression with Python - Part 1
17:43
Logistic Regression with Python - Part 2
16:57
Logistic Regression with Python - Part 3
08:15
Logistic Regression Project Overview
01:36
Logistic Regression Project Solutions
11:05

K Nearest Neighbors

4 lectures
KNN Theory
05:38
KNN with Python
19:39
KNN Project Overview
01:11
KNN Project Solutions
14:14

Decision Trees and Random Forests

5 lectures
Introduction to Tree Methods
06:52
Decision Trees and Random Forest with Python
13:57
Decision Trees and Random Forest Project Overview
03:10
Decision Trees and Random Forest Solutions Part 1
12:13
Decision Trees and Random Forest Solutions Part 2
08:46

Support Vector Machines

4 lectures
SVM Theory
04:36
Support Vector Machines with Python
17:52
SVM Project Overview
02:21
SVM Project Solutions
10:09

K Means Clustering

4 lectures
K Means Algorithm Theory
05:15
K Means with Python
12:35
K Means Project Overview
02:53
K Means Project Solutions
16:38

Principal Component Analysis

2 lectures
Principal Component Analysis
03:26
PCA with Python
16:58

Recommender Systems

3 lectures
Recommender Systems
04:13
Recommender Systems with Python - Part 1
13:36
Recommender Systems with Python - Part 2
13:21

Natural Language Processing

6 lectures
Natural Language Processing Theory
05:06
NLP with Python - Part 1
16:02
NLP with Python - Part 2
18:46
NLP with Python - Part 3
17:30
NLP Project Overview
02:04
NLP Project Solutions
19:26

Neural Nets and Deep Learning

31 lectures
Download TensorFlow Notebooks Here
00:02
Quick Check for Notes
1 question
Welcome to the Deep Learning Section!
00:21
Introduction to Artificial Neural Networks (ANN)
02:15
Installing Tensorflow
00:06
Perceptron Model
10:39
Neural Networks
07:19
Activation Functions
10:39
Multi-Class Classification Considerations
10:34
Cost Functions and Gradient Descent
18:13
Backpropagation
14:47
TensorFlow vs Keras
02:13
TF Syntax Basics - Part One - Preparing the Data
10:48
TF Syntax Basics - Part Two - Creating and Training the Model
13:59
TF Syntax Basics - Part Three - Model Evaluation
12:56
TF Regression Code Along - Exploratory Data Analysis
18:50
TF Regression Code Along - Exploratory Data Analysis - Continued
13:15
TF Regression Code Along - Data Preprocessing and Creating a Model
08:42
TF Regression Code Along - Model Evaluation and Predictions
11:23
TF Classification Code Along - EDA and Preprocessing
08:05
TF Classification - Dealing with Overfitting and Evaluation
16:50
TensorFlow 2.0 Project Options Overview
01:40
TensorFlow 2.0 Project Notebook Overview
07:41
Keras Project Solutions - Dealing with Missing Data
20:35
Keras Project Solutions - Dealing with Missing Data - Part Two
14:46
Keras Project Solutions - Categorical Data
12:02
Keras Project Solutions - Data PreProcessing
17:23
Keras Project Solutions - Data PreProcessing
03:45
Keras Project Solutions - Creating and Training a Model
03:57
Keras Project Solutions - Model Evaluation
09:42
Tensorboard
18:22

Big Data and Spark with Python

12 lectures
Welcome to the Big Data Section!
00:23
Big Data Overview
05:31
Spark Overview
08:59
Local Spark Set-Up
00:59
AWS Account Set-Up
04:13
Quick Note on AWS Security
00:16
EC2 Instance Set-Up
16:18
SSH with Mac or Linux
04:49
PySpark Setup
23:48
Lambda Expressions Review
05:26
Introduction to Spark and Python
08:16
RDD Transformations and Actions
23:08

BONUS SECTION: THANK YOU!

1 lectures
Bonus Lecture
00:10

Đánh giá của học viên

Chưa có đánh giá
Course Rating
5
0%
4
0%
3
0%
2
0%
1
0%

Bình luận khách hàng

Viết Bình Luận

Bạn đánh giá khoá học này thế nào?

image

Đăng ký get khoá học Udemy - Unica - Gitiho giá chỉ 50k!

Get khoá học giá rẻ ngay trước khi bị fix.