Data Analyst Skillpath: Excel, SQL & ML with Python in हिंदी


Be taught information analytics by studying Excel, SQL, Python, Analytics & ML ideas from scratch in Hindi

What you’ll study

Microsoft Excel सीखने वाले सभी नए विद्यार्थियों के लिए कोर्स – इसमें आप Microsoft Excel, Spreadsheets, Formulation, Excel shortcuts, Macros आदि सीखेंगे

Excel के सबसे ज़रूरी और लोकप्रिय Lookup फंक्शन जैसे – Vlookup, Hlookup, Index और Match फंक्शनों को काफी अच्छे से सीख पाओगे ।

SQL की सभी ज़रूरी instructions को सीख पाओगे |

Bar chart, Scatter plots, Histogram आदि का उपयोग करके अपने दर्शकों को आकर्षित कर पाओगे ।

Machine Studying Linear Regression downside के लिए information assortment और information preprocessing की गहराई से जानकारी प्राप्त करोगे |

Description

You’re in search of an entire course on the way to change into a information analyst, proper?

You’ve discovered the fitting Information Analyst Masterclass with Excel, SQL & Python course! This course will train you data-driven decision-making, information visualization, information analytics in SQL, and the usage of predictive analytics like linear regression in enterprise settings.

After finishing this course it is possible for you to to:

  • Grasp Excel’s hottest lookup features akin to Vlookup, Hlookup, Index, and Match
  • Develop into proficient in Excel information instruments like Sorting, Filtering, Information validations, and Information importing
  • Make nice shows utilizing Bar charts, Scatter Plots, Histograms, and so forth.
  • Develop into proficient in SQL instruments like GROUP BY, JOINS, and Subqueries
  • Develop into competent in utilizing sorting and filtering instructions in SQL
  • Discover ways to resolve real-life enterprise issues utilizing the Linear Regression method
  • Perceive the way to interpret the results of the Linear Regression mannequin and translate them into actionable perception

How this course will show you how to?

A Verifiable Certificates of Completion is offered to all college students who undertake this course on Information Analyst Skillpath in Excel, SQL, and Python.

If you’re a pupil, enterprise supervisor, or enterprise analyst, or an government who needs to study Information Analytics ideas and apply information analytics strategies to real-world issues of the enterprise perform, this course will provide you with a stable base for Information Analytics by educating you the preferred information evaluation fashions and instruments

Why do you have to select this course?

We imagine in educating by instance. This course is not any exception. Each Part’s major focus is to show you the ideas by way of how-to examples. Every part has the next parts:

  • Ideas and use instances of various Statistical instruments required for evaluating information analytics fashions
  • Step-by-step directions on implementing information analytics fashions
  • Downloadable information containing information and options used within the course
  • Class notes and assignments to revise and observe the ideas

The sensible courses the place we create the mannequin for every of those methods are one thing that differentiates this course from every other course obtainable on-line.

What makes us certified to show you?

The course is taught by Abhishek (MBA – FMS Delhi, B. Tech – IIT Roorkee) and Pukhraj (MBA – IIM Ahmedabad, B. Tech – IIT Roorkee). As managers within the World Analytics Consulting agency, now we have helped companies resolve their enterprise issues utilizing Analytics and now we have used our expertise to incorporate the sensible points of enterprise analytics on this course. We have now in-hand expertise in Enterprise Evaluation.

We’re additionally the creators of among the hottest on-line programs – with over 1,200,000 enrollments and hundreds of 5-star critiques like these ones:

This is superb, i really like the actual fact the all clarification given will be understood by a layman – Joshua

Thanks Creator for this excellent course. You’re the finest and this course is value any value. – Daisy

Our Promise

Instructing our college students is our job and we’re dedicated to it. You probably have any questions in regards to the course content material, observe sheet, or something associated to any matter, you possibly can all the time put up a query within the course or ship us a direct message.

Obtain Observe information, take Quizzes, and full Assignments

With every lecture, there are class notes hooked up so that you can comply with alongside. It’s also possible to take quizzes to examine your understanding of ideas like Information Analytics in MS Excel, SQL, and Python. Every part accommodates a observe project so that you can virtually implement your studying on Information Analytics.

What is roofed on this course?

The evaluation of knowledge just isn’t the principle crux of analytics. It’s the interpretation that helps present insights after the applying of analytical strategies that makes analytics such an necessary self-discipline. We have now used the preferred analytics software program instruments that are MS Excel, SQL, and Python. It will help the scholars who haven’t any prior coding background to study and implement Analytics and Machine Studying ideas to really resolve real-world issues of Information Evaluation.

Let me offer you a short overview of the course

  • Half 1 – Excel for information analytics

Within the first part, i.e. Excel for information analytics, we’ll discover ways to use excel for data-related operations akin to calculating, remodeling, matching, filtering, sorting, and aggregating information.

We can even cowl the way to use several types of charts to visualise the info and uncover hidden information patterns.

  • Half 2 – SQL for information analytics

IN the second part, i.e. SQL for information analytics, we might be educating you all the things in SQL that you will want for Information evaluation in companies. We are going to begin with fundamental information operations like making a desk, retrieving information from a desk and so forth. In a while, we’ll study superior subjects like subqueries, Joins, information aggregation, and sample matching.

  • Half 3 – Preprocessing Information for ML fashions

On this part, you’ll study what actions you want to take step-by-step to get the info after which put together it for evaluation, these steps are crucial. We begin with understanding the significance of enterprise data then we’ll see the way to do information exploration. We discover ways to do univariate evaluation and bivariate evaluation then we cowl subjects like outlier therapy, lacking worth imputation, variable transformation, and correlation.

  • Half 4 – Linear regression mannequin for predicting metrics

This part begins with easy linear regression after which covers a number of linear regression.

We have now coated the fundamental concept behind every idea with out getting too mathematical about it so that you just perceive the place the idea is coming from and the way it can be crucial. However even in the event you don’t perceive it, it will likely be okay so long as you discover ways to run and interpret the consequence as taught within the sensible lectures.

I’m fairly assured that the course will provide you with the mandatory data on Information Evaluation, and the skillsets of a Information Analyst to right away see sensible advantages in your office.

Go forward and click on the enroll button, and I’ll see you in lesson 1 of this Information Analyst Skillpath course!

Cheers

Begin-Tech Academy

हिन्दी
language

Content material

Introduction

Introduction
Course Assets

Excel Fundamentals

Fundamentals
Milestone!
Worksheet Fundamentals
Information Codecs
Information Dealing with Fundamentals – Reduce, Copy and Paste
Saving and Printing – Fundamentals

Important Formulation

Fundamental Method Operations
Mathematical Features
Distinction between RANK, RANK.AVG and RANK.EQ
Textual Features
Logical Features
Date-Time Features
Lookup Features (V Lookup, Hlookup, Index-Match)

Information Instruments

Information Instruments
Formatting information and tables

Excel Charts

Significance of knowledge visualization
Parts of charts
The Straightforward approach of making charts
Bar and column charts
Formatting Charts
Line Charts
Space Charts
Pie and Doughnut Charts
Scatter plot or XY chart
Waterfall Charts
Sparklines

Pivot desk and Pivot charts

Pivot Tables
Pivot Charts

Macros

Macros

SQL Introduction

Introduction

Set up and getting began

Set up
If pgAdmin just isn’t opening…

Case examine

Case Examine half:1
Case Examine half: 2

Basic SQL statements

CREATE
Train 1 Create DB and Desk
Options to all Workouts
INSERT
Import information from File
Train 2 Inserting and Importing
SELECT assertion
SELECT DISTINCT
WHERE
Logical operators
Train 3 SELECT WHERE
UPDATE
DELETE
ALTER
Train 4 Updating Desk

Restore and Again-up

Restore and Again-up
Debugging restoration points
Creating DB utilizing CSV information
Debugging abstract and Code for CSV information
Train 5 Restore and Again-up

Part instructions: Filtering

IN
BETWEEN
LIKE
Train 6: In, Like & Between

Choice instructions: Ordering

Facet Lecture Commenting in SQL
ORDER BY
LIMIT
Train 7 Sorting

Alias

AS

Combination Instructions

Rely
SUM
AVERAGE
MIN MAX
Train 8 Combination features

Group By Instructions

GROUP BY
HAVING
Train 9 Group By

Conditional Assertion

CASE WHEN

JOINS

Introduction to Joins
Ideas of Becoming a member of and Combining Information
Making ready the info
Internal Be a part of
Left Be a part of
Proper Be a part of
Full Outer Be a part of
Cross Be a part of
Intersect and Intersect ALL
Besides
Union
Train 10 Joins

Subqueries

Half-1 Subquery in WHERE clause
Half-2 Subquery in FROM clause
Half-3 Subquery in SELECT clause
Train 11 Subqueries

Views and Indexes

VIEWS
INDEX
Train 12 Views

String Features

LENGTH
UPPER LOWER
REPLACE
TRIM LTRIM RTRIM
CONCATENATION
SUBSTRING
LIST AGGREGATION
Train 13 String Features

Mathematical Features

CEIL FLOOR
RANDOM
SETSEED
ROUND
POWER
Train 14 Mathematical Features

Date-Time Features

CURRENT DATE TIME
AGE
EXTRACT

Information Sort conversion features

Changing Numbers Date to String
Changing String to Numbers Date

Introduction to Linear Regression

Welcome to the module

Establishing Python and Jupyter Pocket book

Putting in Python and Anaconda
Opening Google colab
Arithmetic operators in Python Python Fundamentals
Strings in Python Half 1
Lists Tuples and Directories Half 1
Working with Numpy Library of Python
Working with Pandas Library of Python
Working with Seaborn Library of Python

Fundamentals of Statistics

Varieties of Information
Varieties of Statistics
Describing information Graphically
Measures of Facilities
Measures of Dispersion

Introduction to Machine Studying

Introduction to Machine Studying

Information Preprocessing

Gathering Enterprise Information
Information Exploration
The Dataset and the Information Dictionary
Importing Information in Python
Univariate evaluation and EDD
EDD in Python
Outlier Therapy
Outlier Therapy in Python
Lacking Worth Imputation
Lacking Worth Imputation in Python
Seasonality in Information
Bi-variate evaluation and Variable transformation
Variable transformation and deletion in Python
Non-usable variables
Dummy variable creation Dealing with qualitative information
Dummy variable creation in Python
Correlation Evaluation
Correlation Evaluation in Python

Linear Regression

The Downside Assertion
Fundamental Equations and Strange Least Squares (OLS) methodology
Assessing accuracy of predicted coefficients
Assessing Mannequin Accuracy RSE and R squared
Easy Linear Regression in Python
A number of Linear Regression
The F – statistic
Deciphering outcomes of Categorical variables
A number of Linear Regression in Python
Take a look at-train break up
Bias Variance trade-off
Extra about test-train break up
Take a look at practice break up in Python
Linear fashions apart from OLS
Subset choice strategies
Shrinkage strategies Ridge and Lasso
Ridge regression and Lasso in Python
The ultimate milestone!

Congratulations & about your certificates

Bonus Lecture

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