An advanced course in data analytics

Data Analytics Master Course

ADMEC Multimedia > Data Science and Analytics Courses > Data Analytics Master Course
Eligibility
Graduation Not Required
Duration
06 Months
Training Type
Classroom, Online

Most Advanced Data Analytics Course Using Statistics, Probability, SQL, Excel, R, Power BI, Tableau, Python (NumPy, Pandas, Matplotlib, SciPy, and Flask).

This 6 months (3 months in fast track) diploma course is designed for beginners to take their analytical thinking to the world’s biggest industries in our classroom and online training. We will start this course from the very basics and slowly-slowly you will be uncovering all the leading data analytical and data visualization languages and software.

As you know that Data Analytics & Visualization is one of the hottest sub-set of Data Science and data analysis using Python and R is in high demand so this course fulfills all the demands of data analysis of the industry from you.

Why we’re on Top in Data Analytics Training Delhi?

  • Across-the-board Curriculum
  • Selected Mentorship
  • Persistent Career Care

Tools and Technologies

 

Tools Covered
  • Statistics
  • Excel
  • SQL
  • Python
  • NumPy
  • Pandas
  • Matplotlib
  • SciPy
  • Flask
  • R Language
  • Power BI
  • Tableau
Key Takeaways
  • Mastering Statistics in Data Analysis
  • Elementary Data Analysis on Excel
  • Understanding SQL As A Query Language
  • Data Analysis Using Python and R Languages
  • Data Analysis and Visualization Using Power BI and Tableau

A professional is incomplete without a strong portfolio. With lifetime placement assistance, we will take care of your resume & portfolio development too.

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Please check out our other Data Analytics courses too:

Entry requirements

Our Data Analytics Master course is for anyone who wants to learn all the leading languages and software used in data analytics and visualization to take out the powerful data points to help industries grow. You must have analytical and logical mindset with 10+2 (intermediate) to be successful in this area.

No programming experience required.

Who can join this course

Do you love huge or big data? Data handling was your area of interest in schools? Then this course is best for you to work with huge data to get some hidden success mantra which provide solutions to businesses to grow in their domains. You are welcome if you have analytical thinking with interest in programming and 10+2 (intermediate) to make businesses succeed.

Career opportunities

Students who successfully completed this course are working as Senior Data Analyst, Python Data Analyst, R Data Analyst, R Developer, Python Expert, Business Analyst, SQL Expert, Excel Expert, Power BI Expert, Tableau Professional etc.

Final projects and tests

You will be working on ‘Data Analytics Project from Scratch’ project with our data analytics expert so that you can prepare yourself to work in the most competitive industry of data analytics after completion of this analytics course.

Course structure and modules

04 Weeks: Module 1

Foundations – Basics of Data Analytics

Part 1 – Introduction

  • Introduction to Data Analytics
  • Data Analytics in Real Life
  • Data Analysis vs Data Analytics
  • Common Tools and Technologies
  • Data and Its Importance
  • Common Steps for Data Analysis

Part II – Math Refresher

  • Useful Concepts of Math
  • Use of Algebra, Geometry, and Calculus in Data Analysis!
  • Data Table, Charts, Graphs etc.

Part III – Statistics

  • Statistics in Data Analysis
  • Types of Statistics
  • Types of Data
  • Categorical Data
  • Numerical Data
  • Association between Categorical & Numerical Variables
  • Correlation and Covariance
  • Hypothesis Testing
  • Advanced Statistical Techniques
    • Multivariate Regression
    • Classification Problems
    • Predictive Analytics
    • Text Analytics

Part IV – Probability

  • Rules of Probability
  • Conditional Probability
  • Random Variables
  • Distributions
  • Combinatorics
  • Bayes Theorem
  • Bayesian Inference

Part V – Data Analysis and Visualization in Excel

  • Functions in Excel
  • Data Analysis
  • Pivot Tables and Lookup
  • Interactive charts
  • What-if-analysis, GOAL SEEK
  • Linking Multiple Sheets
  • Sub Total Reports, Auto Filter
  • Password Protecting Worksheets
  • Dashboard
  • Record a Macro/VBA

Part VI – Data Analytics Essentials of SQL

  • Introduction to DBMS
  • ER diagram
  • Schema design
  • Key constraints & basics of normalization
  • Joins
  • Subqueries involving joins & aggregations
  • Sorting
  • Independent subqueries
  • Correlated subqueries
  • Analytic functions
  • Set operations
  • Grouping and filtering

10 Weeks: Module 2

Data Analytics Practical

Part 1 – Data Analysis with Python

  • Installing and Exploring Python
  • Anaconda
  • Jupyter Notebook
  • NumPy
  • Python Pandas
  • Matplotlib
  • SciPy
  • Flask Framework

Part 2 – Use of R Language in Data Analysis

  • Exploring R Programming Fundamentals
  • Data Manipulation in R
  • Data Modelling in R
  • Variance, Linear Regression, and Logistic Regression in R
  • RStudio
  • Data Visualization with R
  • Project in R

06 Weeks: Module 3

Data Visualization and Insights

Part 1 – Exploring Power BI

  • Introduction to Data Visualization
  • Introduction to Power BI
  • Overview of the Rhyme Interface
  • Importing the Data
  • Fixing the Column Names
  • Transforming the Data
  • Creating Reports
  • Defaults by Education Level
  • Defaults by States
  • Defaulter Ratio and Slicing the Data
  • Project in Power BI

Part 2 – Exploring Tableau

  • Introduction to Tableau
  • Basic charts and dashboard
  • Descriptive Statistics, Dimensions and Measures
  • Visual analytics: Storytelling through data
  • Dashboard design & principles
  • Advanced design components – Improving the dashboards
  • Special types of chart
  • Integrate Tableau with Google Sheets and other data sources
  • Project in Tableau

04 Weeks: Module 4

Domain Exposure
  • Analytics for Marketing & Retail
  • Analytics for Web & Social Media
  • Analytics for Finance & Risk
  • Analytics for Supply Chain & Logistics

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Facilitating the concept of overall development, we organise various events and activities for 360 degree development of our students.

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