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Machine learning & data science With Python

Home Course Machine learning & data science With Python
Machine learning & data science With Python

Machine learning & data science With Python

Course Price: 20000 9999 BDT

Course Duration: 5 moths & 2 months intern (National Faculty)

Weekly: 2 days (8pm)


Accelerate your career with Data Science certification .Data science is an evolutionary technology. So if you update yourself you must gain the depth knowledge of data science for the future of data demand. Data science is popular in Bangladesh.

This course is a perfect blend of theory, case studies and capstone projects. Data Science training is available as online live training

Besides Amazon, eBay, Alibaba, and more other e-commerce websites are building their web applications using data science. In Bangladesh Evely, Daraz, Bkash, Grameenphone, and many other companies use data science.

In all domains, people can learn data science courses in Bangladesh. This field is open to all. The basic skills required to learn data science courses in Bangladesh are some math, statistics, and some programming knowledge.

So if you are interested in Data science training in Bangladesh HR VENTURE is the right place. We ensure you build your skills strong that helps your self-confidence.

HR VENTURE also offers internships after completing the Machine learning and Data Science course in Dhaka.

This course is conducted with international and industrial faculties. All the curriculums are updated with modern curriculum and technologies.

Course Content

Python Programming

Introduction to Python

Installing Python

How Python Code Gets Executed

How Long It Takes To Learn Python

Variables

Receiving Input

Python Cheat Sheet

Type Conversion

Strings

Formatted Strings

String Methods

Arithmetic Operations

Operator Precedence

magic method

If Statements

Logical Operators

Comparison Operators

Weight Converter Program

While Loops

Building a Guessing Game

Building the Car Game

For Loops

Nested Loops

Lists

Essential Machine Learning

Introduction to Machine Learning

Statistical Inference Basics

Python Programming for Machine Learning

Infrastructural Operations in Machine Learning

Supervised Learning: Theory and Use-cases

Unsupervised Learning: Theory and Use-cases

Machine Learning

Recap of Machine Learning Fundamentals

Supervised Learning

Unsupervised Learning

Reinforcement Learning

Dimensionality Reduction and Feature Selection

Introduction to Artificial Neural Networks and Deep Learning

Fundamental Data Science

Recap of Machine Learning Fundamentals

Python working environment

Data types and variables

Data structures in Python

Programming fundamentals

Object-oriented programming more on Functions and Modules

Data Science ecosystem

Tools:

Jupyter Notebook,

Spyder IDE

Advance Data Science Module

Data Science Methodology and Tools

Statistical Analysis

Python for Data Science

SQL for Data Science

Data Wrangling

Data Visualization and Exploratory Data Analysis

Machine Learning in Data Science

Module 01: Statistics for Data Science

A) Descriptive Stats

Central Tendency

Variability

Standardizing

Normal Distribution

Sampling Distributions

B) Inferential Stats

Estimation (Point estimate and Interval estimate)

Hypothesis Testing

T-tests (One Sample, Two Sample Dependent, Two-sample Independent

ANOVA

Chi-square Test

Module 02: Text processing for Data Science

Tokenization

Stemming

Lemmatization

POS tagging

Word embedding

Module 03: Data Analytics using Tableau

Tableau Introduction

Data and connection

Statistical analysis using Tableau

Creating charts

Mapping data in Tableau

Authoring Dashboards

Python packages:

NumPy

Pandas

Matplotlib

SciPy

Scikit-Learn,

TensorFlow,

Keras

Tools:

Jupyter Notebook,

MySQL Workbench