DATA SCIENTIST

DATA SCIENTIST Training provided by DataMites Institute Training Institute in Bangalore,Bommanahalli

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Created by DataMites Institute Training Institute staff Last updated Tue, 17-May-2022 English


DATA SCIENTIST free videos and free material uploaded by DataMites Institute Training Institute staff .

Syllabus / What will i learn?

Data Science Foundation

Introduction To Data Science

Industry Applications

Terminologies

Python Essentials

Anaconda - Python Distribution Installation And Setup

Jupyter Notebook

Python Basics

Data Structures

Control Statements

R Language Essentials

R Installation And Setup

R Studio Basics

R Data Structures

Control Statements

Data Science Package

Maths For Data Science

Essential Mathematics

Linear Algebra

Linear Transformation

Types Of Matrices, Matrix Properties, And Operations Probability And Calculus

Statistics For Data Science

Statistics Introduction

Terminologies

Inferential Statistics

Harnessing Data

Exploratory Analysis

Distributions

Central Limit Theorem

Hypothesis Testing

Correlation, And Regression

Data Preparation With Pandas

Numpy Array Functions

Data Munging With Pandas

Imputation

Outlier Analysis

Visualization With Python

Visualization Basics

Matplotlib Introduction

Basic Plots

Customizing Plots

Sub-Plots

Statistical Plots

Seaborn Package Introduction

Machine Learning Associate

Machine Learning Introduction

Ml Core Concepts

Unsupervised And Supervised Learning

Clustering With K-Means

Linear Regression

Logistic Regression

K-Nearest Neighbor

Advanced Machine Learning

Bayes Theorem

Naïve Bayes Algorithm For Text Classification,

Decision Tree

Ensemble Methods: Random Forest,

Extra Trees

Svm, Boosting Techniques

Xgboost

Artificial Neural Network

Adv Metrics

Imbalanced Dataset

Grid Search

K-Fold Cross-Validation

dation

Sql For Data Science

Relational Database Management Systems Basics

Sql Introduction

Connection To Sql Databases

Fetching Data With Select

Where Condition

Sql Joins

Sql Crud Operations

Deep Learning – Cnn Basics

Deep Learning Introduction

Tensorflow And Keras

Convolution Neural Network Basics

End To End Image Classification Of Cats And Dogs Using The Tensorflow-Keras Platform.

Tableau Associate

Visual Analytics Basics

Tableau Introduction

Connecting To Datasource

Dimensions Vs Measures

Basic Plots

Compound Plots

Forecasting

Publishing

Ml Model Deploy- Flask Api

Ml Deployment Strategies

Flask Introduction

Packing Training Ml Model

Deploying It On Flask As Api

Data Science Project Execution

Data Science Project Management Method

Business Case Risk

Limitation Of Machine Learning

Project Pitfalls.

Big Data Foundation

Introduction to Big Data

Hadoop Concepts

Spark Big Data for Data Science Processing

Handling Big Data in Machine Learning Pipeline.

 

 



Curriculum for this course
0 Lessons 00:00:00 Hours
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Description

These four facets form four pillars for the data science field. They are 1. Programing 2. Statistics 3. Machine Learning 4. Business Knowledge.

The course is mainly focussed on Python for core data science programming, it also includes R as necessary to enable professionals working in R.

Statistics are covered as required for a Data Scientist, you may find a detailed syllabus in syllabus tab.

Machine Learning is the main tool kit for Data Science in predicting classification or regression.

This course courses all popular ML algorithms as detailed in the syllabus tab.

This course allows candidates to obtain an in-depth knowledge by laying a strong foundation and covering all the latest data science topics.

The increasing demand curve for data science professionals to manage the large set of data in various organizations providing millions of job opportunities in global markets.

The knowledge gained through this course along with IABAC™ certificate surely helps you to become a data science professional

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