Data Science

Course Instructor: TECHU

FREE

Course Overview

Schedule of Classes

Start Date & End Date

Nov 27 2025 - May 26 2026

Total Classes

202 Classes

Course Curriculum

1 Subject

Data Science

88 Learning Materials

Advanced Excel

Basics of Excel

PDF

Cell References

PDF

Data Validation_Password_Blankrow deletion

PDF

LookUps

PDF

Logical Functions

PDF

Date Time functions

PDF

Text Functions

PDF

Sumif(s)_countif(s)_averageif(s)

PDF

Dynamic Arrays

PDF

Random Numbers Conditional Formating

PDF

Tasks in Conditional Formatting

PDF

Charts

PDF

Errors

PDF

FlashFill

PDF

Cross Sheet Refs_Pivot Tables

PDF

Pivot Use Cases

PDF

Scenario Manager_Goal Seek

PDF

Slicers

PDF

DashBoards

PDF

Advanced Excel Data Files

Conditional Formatting

DOC

Copy Visible Cells only

DOC

Delete Blank rows

DOC

Dynamic Arrays

DOC

Finding Duplicates

DOC

Find_&_Select

DOC

Inventory_Pivot

ZIP

IT_Helpdesk Support

DOC

Marketing_Pivot

ZIP

Pivot Tables

DOC

Remove Duplicates

DOC

Retails Sales Data

DOC

Sales Analysis Pivot

DOC

Slicers

DOC

Sort Function

DOC

Python

Introduction to python

DOC

Steps of Programming and Use cases

DOC

Executable Commands and Literals

DOC

Study Material on Executable Commands and Literals

DOC

Data Types

DOC

Study Material on Data Types

DOC

Operators

DOC

Control Statements

DOC

Stydy Material o Control Statements

DOC

Loops

DOC

Study Material on Loops

DOC

Functions and Arguments

DOC

Study Material on Functions

DOC

Modules and OOPs Concepts

DOC

Study Material on Modules and OOPs Concepts

DOC

Exceptional Handling

DOC

Study Material on Exceptional Handling

DOC

File Handling

DOC

MySQL

Introduction to MySQL

DOC

Data types and Constrains

DOC

Sublanguages and Clauses

DOC

logical_Operators&Sample Questions

DOC

Special_Operators&Sample Questions

DOC

Functions

DOC

Group_By& Filtering

DOC

SubQueries_1

DOC

SubQueries_2

DOC

SubQueries_types

DOC

Use case Scenario

DOC

Joins

DOC

Co-related SubQueries

DOC

Single row functions

DOC

Statements_Sublanguages

DOC

Normalization

DOC

Natural Language Processing

Natural Language processing

ZIP

Machine Learning and Deep Learning

Introduction to Machine Learning

DOC

Data Training Process

DOC

K_ Nearest Neighbours

DOC

Decision Tree Algorithm

DOC

Linear and Multiple linear Regression

DOC

Logistic Regression

DOC

Bagging and Random Forest Algorithm

DOC

Support Vector Machines (SVM)

DOC

Ada Boost and Gradient Boost Algorithm

DOC

Cat Boost and XG Boost Algorithm

DOC

Boosting and Types of Boosting Algorithms

DOC

Unsupervised Learning

DOC

K_Means Clustering

DOC

Hierarchical Clustering and its Types

DOC

DB Scan Clustering

DOC

Principal Compound Analysis (PCA)

DOC

Neural Networks -Deep Learning

DOC

Convolutional Neural Networks (CNN)- Deep Learning

DOC

Recurrent Neural Networks(RNN) and LSTM - Deep Learning

DOC

Excel

Look Ups in Excel

Logical Functions

Date and Time Functions

Text Functions

Python(Operators)

Python( Conditional Statements)

Python (Modules)

MySQL(Basics)

MySQL(Data Types and Constrains)

MySQL( Sub-languages and Clauses )

MySQL ( Groupby_Filters_Subqueries)

MySQL (Functions)

MySQL( Special Operators)

MySQL( Logical Operators)

Course Instructor

TECHU

6 Courses • 95 Students