Name: Learn Data Science Beginner Course Free
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Course Curriculum

117 Lectures | 12:22:46

What is Data Science?

06:46
Learn data science for beginners

16:19
Install python on windows

03:52
Variables in python

03:42
Variables in python Exercise
Numbers

08:44
Numbers Exercise
Strings

07:11
Strings Exercise
Lists

10:23
List Exercise
Install PyCharm on Windows

06:33
Debug Python code using PyCharm

09:38
If Statement

13:18
For loop

20:40
For Loop Exercise
Functions

16:09
Functions Exercise
Dictionaries and Tuples

08:46
Dictionaries and Tuples Exercise
Install Python Module (using pip)

03:07
Modules

11:03
Working With JSON

08:42
if __name__ == "__main__"

04:25
Exception Handling

09:10
Class and Objects

09:50
What is Jupyter Notebook?

08:25
What is Anaconda? Install Anaconda On Windows.

05:22
Jupyter Notebook Tutorial / Ipython Notebook Tutorial

24:08
numpy tutorial - basic array operations

13:48

What is Pandas python? Introduction and Installation

09:23
Dataframe Basics

20:58
Different Ways Of Creating DataFrame

07:40
Read Write Excel CSV File

27:03
Handle Missing Data: fillna, dropna, interpolate

22:07
Handle Missing Data: replace function

13:21
Group By (Split Apply Combine)

10:34
Concat Dataframes

15:14

Introduction and Installation

06:59
format strings in plot function

06:18
Axes labels, Legend, Grid

06:58
Bar Chart

08:45
Histograms

08:19
Pie Chart

06:26

How to become a data scientist for free? | Step by step approach to become data scientist

10:33
What is Machine Learning?

06:51
Linear Regression Single Variable

15:14
Linear Regression Single Variable Quiz
Linear Regression Single Variable Exercise
Linear Regression Multiple Variables

14:08
Linear Regression with Multiple Variables Quiz
Linear Regression Multiple Variables Exercise
Gradient Descent and Cost Function

28:26
Gradient Descent and Cost Function Quiz
Gradient Descent and Cost Function Exercise
Save Model Using Joblib And Pickle

08:22
Dummy Variables & One Hot Encoding

21:35
Dummy Variables & One Hot Encoding Quiz
Dummy Variables & One Hot Encoding Exercise
Training and Testing Data

06:34
Logistic Regression (Binary Classification)

19:19
Logistic Regression (Binary Classification) Quiz
Logistic Regression (Binary Classification) Exercise
Logistic Regression (Multiclass Classification)

15:43
Logistic Regression (Multiclass Classification) Exercise
Decision Tree

14:46
Decision Tree Exercise
Support Vector Machine (SVM)

23:22
Support Vector Machine (SVM) Exercise
Support Vector Machine Quiz
Random Forest

12:49
Random Forest Exercise
Random Forest Quiz
K Fold Cross Validation

25:20
K Fold Cross Validation Exercise
K Fold Cross Validation Quiz
K Means Clustering

25:15
K Means Clustering Exercise
K Means Clustering Quiz
Naive Bayes Part 1

13:38
Naive Bayes Part 2

11:29
Naive Bayes Quiz
Hyper parameter Tuning (GridSearchCV)

16:30
Hyper parameter Tuning (GridSearchCV) Quiz
Hyper parameter Tuning (GridSearchCV) Exercise
L1 and L2 Regularization | Lasso, Ridge Regression

19:21
L1 and L2 Regularization | Lasso, Ridge Regression Quiz

Introduction

02:12
Data Cleaning

15:21
Feature Engineering

08:26
Outlier Removal

19:31
Model Building

19:21
Python Flask Server

21:13
Website or UI

13:21
Deploy machine learning model to production AWS

28:38
Data Analyst vs Data Engineer vs Data Scientist

10:52

Introduction

04:42
Data Collection

05:37
Data Cleaning

40:45
Feature Engineering

18:23
Training a Model

20:01
Flask Server

36:16
Build Website

38:14
Deployment & Exercise

05:17

Introduction

03:39
Why deep learning is becoming so popular?

05:25
What is a neuron?

16:49
What is a Neural Network

11:01
Install tensorflow 2.0

02:37
Pytorch vs Tensorflow vs Keras

02:17
Neural Network For Handwritten Digits Classification

36:39
Activation Functions

16:29
Derivatives

12:35
Derivatives Exercise
Matrix Basics

11:42
Matrix Basics Exercise
Loss or Cost Function

24:37
Loss or Cost Function Exercise
Gradient Descent For Neural Network

41:34
Implement Neural Network In Python

13:23
Stochastic Gradient Descent vs Batch Gradient Descent vs Mini Batch Gradient Descent

36:47
Stochastic Gradient Descent vs Batch Gradient Descent vs Mini Batch Gradient Descent Exercise
Chain Rule

14:06
Tensorboard Introduction

14:56
GPU bench-marking with image classification

23:58
GPU bench-marking with image classification Exercise
Customer churn prediction using ANN

40:41
Customer churn prediction using ANN Exercise
Precision, Recall, F1 score, True Positive

11:46
Handling imbalanced dataset in machine learning

38:26
Handling imbalanced dataset in machine learning Exercise
Applications of computer vision

09:44
Simple explanation of convolutional neural network

23:54
Image classification using CNN (CIFAR10 dataset)

28:12
Image classification using CNN (CIFAR10 dataset) Exercise
Convolution padding and stride

06:53
Data augmentation to address overfitting

31:33
Transfer Learning

25:55
Image classification vs Object detection vs Image Segmentation

02:32
Popular datasets for computer vision: ImageNet, Coco and Google Open images

13:02
Sliding Window Object Detection

04:58
What is YOLO algorithm?

16:04
Object detection using YOLO v4 and pre trained model

14:53
What is Recurrent Neural Network (RNN)?

16:00
Types of RNN | Recurrent Neural Network Types

03:43
Vanishing and exploding gradients

09:53
Simple Explanation of LSTM

14:37
Simple Explanation of GRU (Gated Recurrent Units)

08:15
Bidirectional RNN

05:50
Converting words to numbers, Word Embeddings

11:31
Word embedding using keras embedding layer

21:34
What is Word2Vec?

18:27
Implement word2vec in gensim

18:40
Distributed Training On NVIDIA DGX Station A100

14:46
Tensorflow Input Pipeline

33:19
Tensorflow Input Pipeline Exercise
Optimize Tensorflow Pipeline Performance: prefetch & cache

26:16

Let’s See

What you'll learn

Python
Jupyter Notebook
Numpy
Pandas
Matplotlib for data visualization
Machine Learning using sklearn
Deep learning using tensorflow 2.0

Meet your

Course Instructor

Dhaval Patel

Data Entrepreneur | Youtuber | Ex - Bloomberg, NVIDIA

I have 17 years of experience in programming and data science working for big tech companies like NVIDIA and Bloomberg. I also run a famous youtube channel called Codebasics where I pursue my passion for teaching. Codebasics is one of the top channels on youtube when it comes to data science, machine learning, data structures, etc. I firmly believe that “Anyone can code” and I use analogies, simple explanations, and step-by-step storytelling to explain difficult concepts in such a way that even a high school student can understand them easily.

Free

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What's Included

12:22:46 on-demand video

117 Lectures

28 Assignments

12 Quizzes

Access on tablet and phone

Free Lifetime Access

Learn Data Science Beginner Course Free

Free

Course Curriculum

1. Data Science Full Course For Beginners 30 Lectures

2. Python Pandas Tutorial 8 Lectures

3. Matplotlib Tutorial 6 Lectures

4. Machine Learning Tutorial Python 43 Lectures

5. Machine Learning & Data Science Project - Real Estate Price Prediction Project 9 Lectures

6. Data Science & Machine Learning Project - Image Classification 8 Lectures

7. Deep Learning Tutorial 53 Lectures

Let’s See

What you'll learn

Meet your

Course Instructor

Dhaval Patel

Free

What's Included