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Data analytics course
Crack 10+ LPA jobs with our Data Analytics Course!
Instructor: Aryan Singh
Language: Hindi
Validity Period: Lifetime
$99 60% OFF
$39 including 18% GST
10% Cashback as 30DC Coins
Become a Job-Ready Data Analyst: The Complete Course
➡️ One-Time Payment, Lifetime Access: Your complete, career-long toolkit for data analytics. Always updated.
➡️ Join 20,000+ Aspiring Analysts: Learn with a massive community of data professionals and career-changers.
➡️ Build a Portfolio of 5+ Real-World Analyses: Solve real business problems and create a portfolio that gets you hired.
➡️ Earn Your Data Analytics Certificate: Get a professional credential proving your mastery of the complete analytics workflow.
What You'll Learn
➡️ The Analyst Mindset & Essential Statistics:
▸ Thinking Like an Analyst: Learn the structured frameworks used to solve business problems with data.
▸ Foundational Statistics: Master descriptive stats (mean, median, mode), distributions, and the core principles of hypothesis testing.
➡️ Excel: From Beginner to Power-User:
▸ Data Wrangling: Clean, sort, and filter messy data with functions like VLOOKUP, IF, and XLOOKUP.
▸ Advanced Analysis: Uncover insights quickly with Pivot Tables, Power Query, and what-if analysis.
➡️ SQL: The Language of Data:
▸ Database Fundamentals: Understand how relational databases work.
▸ Querying with Confidence: Go from basic SELECT statements to complex JOINs, aggregations, and subqueries.
▸ Advanced SQL: Use window functions and CTEs to perform sophisticated analyses directly in the database.
➡️ Python for Data Analysis:
▸ Pandas for Data Manipulation: Master the most powerful library for cleaning, transforming, and exploring datasets.
▸ NumPy for Calculations: Perform complex numerical operations efficiently.
▸ Data Visualization with Matplotlib & Seaborn: Create compelling charts and graphs to tell stories with your data.
➡️ Power BI for Data Visualization & Dashboards:
▸ Connecting & Transforming Data: Import data from any source (Excel, SQL, etc.) and prepare it for analysis.
▸ DAX Fundamentals: Learn the Data Analysis Expressions language to create powerful custom calculations and measures.
▸ Building Interactive Dashboards: Design and publish professional, interactive dashboards that empower business users to explore data on their own.
Build a Portfolio of Real-World Analyses
➡️ Go Beyond Theory: You will apply your full skill set to 5+ projects that mirror the challenges you'll face on the job, creating a portfolio that proves your value.
➡️ Solve Real Business Problems:
▸ Executive Sales Dashboard: Use Power BI to build an interactive dashboard analyzing sales performance against targets for executive review.
▸ Customer Segmentation Analysis: Use SQL and Python to group customers by behavior and provide actionable marketing recommendations.
▸ Marketing Campaign ROI Analysis: Investigate the effectiveness of a marketing campaign to determine its return on investment.
▸ Web Analytics Deep Dive: Analyze website traffic data to identify user drop-off points and suggest UI/UX improvements.
Career & Job Support
➡️ Job-Ready Curriculum: Our course is designed around the skills and tools listed in thousands of real data analyst job descriptions.
➡️ Technical Interview Prep: Get dedicated modules on acing SQL queries, Python coding challenges, and business case study interviews.
➡️ Portfolio & Resume Reviews: Get expert guidance on building a data-focused resume and a portfolio website that gets noticed by recruiters.
Ready to turn data into decisions and launch your analytics career? Let's get started!
| Intro to data analytics | |||
| [New] Projects addition at the end | |||
| Who is Data Analyst and Data Analyst Roadmap 14:00 | |||
| 15+ Interview, Revision guides and notes | |||
| Data Analytics course material | |||
| Data Analytics guide | |||
| Data engineering roadmap | |||
| Additional Interview, Revision guides and notes | |||
| Excel Notes | |||
| Stats Notes | |||
| SQL Notes | |||
| [NEW] Quick Data Analyst masterclasses - Dr.Ashok | |||
| Video1 Introduction to Data Analytics 37:00 | |||
| Video2 Essential Tools and Technologies 32:00 | |||
| Video3 Data Collection and Cleaning 40:00 | |||
| Video4 Exploratory Data Analysis 45:00 | |||
| Video5 Statistical Analysis and Hypothesis Testing 40:00 | |||
| Video6 Data Visualization Techniques 38:00 | |||
| Excel course | |||
| What is Excel 1:00 | |||
| Uses 2:00 | |||
| Startup Screen 3:00 | |||
| Ribbons 4:00 | |||
| Tricks | |||
| Workbook | |||
| Syntax 1:00 | |||
| Cell Selection 2:00 | |||
| Cell Copy 1:00 | |||
| Fill in different ways 3:00 | |||
| Click to Fill 3:00 | |||
| full range select 2:00 | |||
| drag , drop , copy 3:00 | |||
| Adding New Column and Row 1:00 | |||
| Delete Cell 1:00 | |||
| Undo / Redo 1:00 | |||
| Fomulas 3:00 | |||
| Relative 2:00 | |||
| Absolute 1:00 | |||
| Sum 1:00 | |||
| Sub | |||
| Multiply | |||
| Divide | |||
| Parentheses 2:00 | |||
| bold | |||
| italic | |||
| underline | |||
| Fill color | |||
| font color | |||
| font size | |||
| font style | |||
| Format Painter 1:00 | |||
| Colors 4:00 | |||
| Borders 3:00 | |||
| [NEW] Quick Python masterclass | |||
| 1 Python introduction with AI 5:00 | |||
| 2 Variables, functions, lists, tuple 8:00 | |||
| 3 For loops, if else, conditionals 4:00 | |||
| 4 Exploring Flask backend with Python 7:00 | |||
| 5 Explore Python and AI to do anything 8:00 | |||
| [NEW] Python Detailed Course | |||
| Overview | |||
| Installation , First Program and Variables 22:00 | |||
| Operators and Data Types_ int, float, complex, str, bool 21:00 | |||
| String , Lists and Escape Seq 25:00 | |||
| if , if else , elif and ternary 13:00 | |||
| Tuple , more methods and Unpacking 16:00 | |||
| Sets and Dictionary 27:00 | |||
| looping _ While and For 20:00 | |||
| Functions 11:00 | |||
| Higher order Function , recursion and lambda 13:00 | |||
| Class , objects and Inheritance 16:00 | |||
| Python course | |||
| 1 Introduction to Python 8:00 | |||
| 2 IDE , Google Colab 3:00 | |||
| 3 Comments 1:00 | |||
| 4 Basic Numeric 2:00 | |||
| 5 Variables | |||
| 6 Data type , Strings 11:00 | |||
| 7 List | |||
| 8 Tuple | |||
| 9 Dictionaries | |||
| 10 Sets | |||
| 11 Indexing 6:00 | |||
| 12 Slicing | |||
| 13 Arithmetic Operator 2:00 | |||
| 14 Comparison Operator 1:00 | |||
| 15 Logical Operators 2:00 | |||
| 16 Assignment Operator 2:00 | |||
| 17 Membership Operator | |||
| 18 List Concat and Multiplying | |||
| 19 String Concat and Multiplying | |||
| 20 Copy Dictionary | |||
| 21 Clear | |||
| 22 set union, intersection, difference | |||
| 23 Input Function 3:00 | |||
| 24 Help Function | |||
| 25 Round function 1:00 | |||
| 26 Sum Function | |||
| 27 Absolute Function | |||
| 28 Enumerate Function 1:00 | |||
| 29 zip Function 1:00 | |||
| 29 zip Function 1:00 | |||
| 30 Converting Data Types 2:00 | |||
| 31 Length Method | |||
| 32 Find Index | |||
| 33 Get | |||
| 34 Find | |||
| 35 Count | |||
| 36 More Dictionary Method 2:00 | |||
| 37 Sorting List | |||
| 38 Append | |||
| 39 update 1:00 | |||
| 40 replace | |||
| 41 Extend | |||
| 42 Insert | |||
| 43 set Default | |||
| 44 String Functions 4:00 | |||
| 45 _ Conditional - if else 3:00 | |||
| 46 _ elif 1:00 | |||
| 47 _ For in Loop 6:00 | |||
| 48 _ Range 7:00 | |||
| 49 _ While Loop 5:00 | |||
| 50 _ Functions 6:00 | |||
| 51 _ Arbitrary Arguments 2:00 | |||
| 52 _ Key value type of argument 2:00 | |||
| 53 _ Arbitrary Keyword Argument 1:00 | |||
| 54 _ Passing List as an Argument 1:00 | |||
| 55 _ Return 2:00 | |||
| 56 _ pass | |||
| 57 _ lambda 4:00 | |||
| 58 _ Filter 2:00 | |||
| 59 _ map 3:00 | |||
| 60 _ class objects 4:00 | |||
| 61 _ constructor 4:00 | |||
| 62 _ methods using class 2:00 | |||
| 63 _ Polymorphism 8:00 | |||
| 64 _ Inheritance and Super 5:00 | |||
| Web Scrapping using Python | |||
| Introduction 14:00 | |||
| Prerequisites , tools 1:00 | |||
| Rules for webscrapping 1:00 | |||
| request module 1:00 | |||
| client server in web scrapping 3:00 | |||
| editor and module install 5:00 | |||
| get post 5:00 | |||
| request get 4:00 | |||
| SQL Course | |||
| 1 _ What is Database and Why Database 4:00 | |||
| 2 _ What is SQL 3:00 | |||
| 3_ SQL vs MySQL 5:00 | |||
| 4 _ Installation 5:00 | |||
| 5 _ Show databases 1:00 | |||
| 6_ Create Database 1:00 | |||
| 7 _ Delete Database | |||
| 8 _ Use Database | |||
| 9 _ Tables 1:00 | |||
| 10 _ Data Types 6:00 | |||
| 11 _ Create Table 6:00 | |||
| 12 _ Delete Table | |||
| 13 _ Comments | |||
| 14 _ Insert value into Table 2:00 | |||
| 15 _ Select all | |||
| 16 _ Insert Multiple Values 2:00 | |||
| 17 _ Null 5:00 | |||
| 18 _ Default 2:00 | |||
| 19 _ Distinct 2:00 | |||
| 20 _ Where 2:00 | |||
| 21 _ Order By 2:00 | |||
| 22 _ AND Operator 5:00 | |||
| 23 _ OR Operator | |||
| 24 _ Not Operator | |||
| 25 _ Update Table 1:00 | |||
| 26 _ Update Warning | |||
| 27 _ Remove 1:00 | |||
| 28 _ Limit 2:00 | |||
| 29 _ MIN MAX 1:00 | |||
| 30 _ Count 2:00 | |||
| 31 _ Average 1:00 | |||
| 32 _ Sum | |||
| 33 _ Like 4:00 | |||
| 34 _ In 1:00 | |||
| 35 _ Between 2:00 | |||
| 36 _ Primary Key 5:00 | |||
| 37 _ Auto Increment 3:00 | |||
| 38 _ Concat 2:00 | |||
| 39 _ Substring 2:00 | |||
| 40 _ Replace 1:00 | |||
| 41 _ Reverse 2:00 | |||
| 42 _ Upper | |||
| 43 _ Lower | |||
| 44 _ Insert 1:00 | |||
| 45 _ Trim | |||
| 46 _ Unique 3:00 | |||
| 47 _ Check 2:00 | |||
| 48 _ Name 1:00 | |||
| 48 _ Name 1:00 | |||
| 49 _ Alter column 1:00 | |||
| 50 _ Alter Drop | |||
| 51 _ Alter Modify | |||
| Complete Statistics mastery | |||
| What is Statistics and Its Types 7:00 | |||
| Individuals and Variables 2:00 | |||
| Population and Sample 3:00 | |||
| Qualitative vs Quantitative 7:00 | |||
| Level Of Measurment 5:00 | |||
| Notation | |||
| Prameter vs Statistic | |||
| Surveys , Experiments , Observation 2:00 | |||
| Different Types of Sampling 9:00 | |||
| Data Primary and Secondary 4:00 | |||
| Sampling Error and Bias 5:00 | |||
| Probability 4:00 | |||
| Non negative 1:00 | |||
| All possible 1 | |||
| Complement 1:00 | |||
| Addition Theorem 2:00 | |||
| Mutually Exclusive 4:00 | |||
| Non Mutually Exclusive 2:00 | |||
| Multiplication Theorem Independent and Not Independent 7:00 | |||
| Bayes Theorem 11:00 | |||
| Mean 2:00 | |||
| Median 3:00 | |||
| Range | |||
| Mode | |||
| Variance and Standard Derivation 4:00 | |||
| Percentile 6:00 | |||
| Combination 7:00 | |||
| Power BI course | |||
| What is Power BI 3:00 | |||
| Importance and Some Uses 2:00 | |||
| Installation and Quick Overview 3:00 | |||
| Connect to CSV File 3:00 | |||
| Get Data from Excel | |||
| Theme and Save custom theme | |||
| More on Formatting 4:00 | |||
| Legend , X axis ,Y axis | |||
| More Charts Table etc | |||
| Creating A Graph | |||
| Preview Option | |||
| IncludeExclude 1:00 | |||
| Table | |||
| Pie Chart , Donut Chart 4:00 | |||
| Waterfall chart 7:00 | |||
| TreeMap 2:00 | |||
| Line Chart 2:00 | |||
| Ribbon 2:00 | |||
| Funnel 4:00 | |||
| Maps 2:00 | |||
| Table and Conditional Formatting 9:00 | |||
| [Masterclasses] Data Analyst masterclasses | |||
| Excel Mastery Beginner to Advanced 49:00 | |||
| SQL Class 18:00 | |||
| Introduction to Pandas | |||
| Data Visualization Masterclass 38:00 | |||
| Data Preprocessing Essentials | |||
| Mastering Data Analysis with Python | |||
| Mastering Linux Commands 8:00 | |||
| Data analytics project | |||
| Netflix Dashboard 26:00 | |||
| Sales dashboard 24:00 | |||
| Power BI Full Project - Sales Dashboard | |||
| 0 Overview 2:00 | |||
| [Sales Data] | |||
| 1 Data | |||
| 2 sales dashboard 2:00 | |||
| 3 Product name , city , sale 5:00 | |||
| 4 totals 4:00 | |||
| 5 Consumer , products 1:00 | |||
| 6 pie cahrt 4:00 | |||
| 7 donut chart | |||
| 8 sum of sales and profits 1:00 | |||
| 9 final | |||
| Power BI Full Project - Netflix Dashboard | |||
| 0 Overview 1:00 | |||
| Netflix dashboard | |||
| 1 Background 3:00 | |||
| 2 . Totals 7:00 | |||
| 3 rating by shows | |||
| 4 count of shows 3:00 | |||
| 5 map 3:00 | |||
| 6. release dates 1:00 | |||
| Data Analyst Handwritten Notes | |||
| Python-Handwritten-Notes 🔥 (64 pages) | |||
| SQL Handwritten Notes💡 (41 pages) | |||
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