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Wednesday, March 3, 2021


Elsword is a free-to-play, online action RPG that uses classic side-scrolling beat ‘em up gameplay mechanics and deep customization to bring a unique manga experience to life.

In Elsword, you star in your own comic book while experiencing all the excitement of a massively multiplayer online game. Get ready for fast-paced gameplay, stunning animation, and epic bosses. Whether conquering hordes of enemies in dungeon runs or showing off your skills in the PvP arena, Elsword is the most intense free-to-play action RPG to date.
Key Features

  • Co-Op Gameplay - Party-up with friends to explore over 50 unique and beautifully rendered dungeons, towns, and secret levels.

  • Unique Characters, Unique Stories- Players can choose from thirteen customizable characters, each their own unique story, play style and special skills to develop.

  • Skill-Based PVP Combat- Elsword offers intense and strategic PvP with matchmaking and multiple competitive modes. Challenge your friends in matches of up to 8 players at a time.

  • Customize like Crazy- Each character features multiple job changes, dozens of skills and endless opportunities for customization. Create or discover your personal look.

  • Community Support- Constant game updates, item and content expansions, and special events including GM Livestream play sessions, community contests and PVP Tournaments are all a part of the Elsword experience.

Click here to download

Monday, January 25, 2021

The Data Science Course 2020 Complete Data Science Bootcamp Training

Course Detail:

Part 1 Introduction

The Field of Data Science - The Various Data Science Discipline

The Field of Data Science - Connecting the Data Science Disciplines

The Field of Data Science - The Benefits of Each Disciplines

The Field of Data Science - Popular Data Science Techniques

The Field of Data Science - Popular Data Science Tools

The Field of Data Science - Careers in Data Science

The Field of Data Science - Debunking Common Misconceptions

Part 2 Probability

Probability - Combinatorics

Probability - Bayesian Inference

Probability - Distributions

Probability - Probability in Other Fields

Part 3 Statistics

Statistics - Descriptive Statistics

Statistics - Practical Example Descriptive Statistics

Statistics - Inferential Statistics Fundamentals

Statistics - Inferential Statistics Confidence Intervals

Statistics - Practical Example Inferential Statistics

Statistics - Hypothesis Testing

Statistics - Practical Example Hypothesis Testing 

Part 4 Introduction to Python

Python - Variables and Data Types

Python - Basic Python Syntax

Python - Other Python Operators

Python - Conditional Statements

Python - Python Functions

Python - Sequences

Python - Iterations

Python - Advanced Python Tools

Part 5 Advanced Statistical Methods in Python

Advanced Statistical Methods - Linear regression with StasModels

Advanced Statistical Methods - Multiple Linear Regression with StatsModels

Advanced Statistical Methods - Linear Regression with sklearn

Advanced Statistical Methods - Practical Example Linear Regression

Advanced Statistical Methods - Logistic Regression

Advanced Statistical Methods - Cluster Analysis

Advanced Statistical Methods - K-Means Clustering

Advanced Statistical Methods - Other Types of Clustering

Part 6 Mathematics

Part 7 Deep Learning

Deep Learning - Introduction to Neural Networks

Deep Learning - How to Build a Neural Network from Scratch with NumPy

Deep Learning - TensorFlow 2.0 Introduction

Deep Learning - Digging Deeper into NNs Introducing Deep Neural Networks

Deep Learning - Overfitting

Deep Learning - Initialization

Deep Learning - Digging into Gradient Descent and Learning Rate Schedules

Deep Learning - Preprocessing

Deep Learning - Business Case Example

Deep Learning - Conclusion

Appendix Deep Learning - TensorFlow 1 Introduction

Appendix Deep Learning - TensorFlow 1 Classifying on the MNIST Dataset

Appendix Deep Learning - TensorFlow 1 Business Case

Software Integration

Case Study - What's Next in the Course

Case Study - Preprocessing the 'Absenteeism Data'

Case Study - Applying Machine Learning to Create the 'absenteeism module'

Case Study - Loading the 'absenteeism module'

Case Study - Analyzing the Predicted Outputs in Tableau

Bonus lecture

View The Data Science Course Here