Explore Our Comprehensive Training Curriculum on Data Analyst
Discover the full potential of Data Analyst, one of the most essential tools in today’s market. Whether you're looking to build cutting-edge applications, enhance your skills, or explore new career opportunities, Data Analyst offers everything you need. Our training curriculum provides a comprehensive overview, covering all key aspects from the fundamentals to advanced techniques. Learn how to leverage Data Analyst to create real-world solutions, gain hands-on experience with industry-standard tools, and stay ahead of the curve in an ever-evolving landscape. Join us and take the next step in mastering Data Analyst!"
Tools & Technologies You’ll Master in Data Analyst Course
💳 Course Purchase Info
Everything you need to know before enrolling
- ⏱️ Duration: 140 Hours
- 📚 Modules: 8
- 👥 Students: 40
- 🎯 Level: Beginner
- 🗣️ Language: English
Industry-Aligned Curriculum for This Course
Explore each topic in-depth through interactive sessions, real-world use cases, and tool-based learning. You’ll not only understand the theory but also build practical skills that matter in actual roles.
30+
Case Studies & Projects
Yes
Certificate of Completion
100%
Career Support & Guidance
Key Highlights in Data Analyst Course
Every Feature Empowers The Career You’ve Always Wanted
80% Practical Training
2 Global Certifications
Integrated Internship
Personalised Career Coach
Instant Doubt Solving
Alumni Network
Multi-Domain Interviews
Profile Building Session
📘 Curriculum Overview
Module 1: Power BI 20 Hours for this Module
+Introduction to DAX
Basic DAX Functions
What is Power BI?
Introduction to Business Intelligence tools
Installation of Power BI Desktop
Power BI Desktop
Power BI Gateway
Power BI Mobile Apps
Power BI Service
Databases
Import vs DirectQuery
Azure Integration
Online Services
Power BI vs Tableau
Power BI vs SSRS
Data Modeling and Navigation
Report, Data, Relationships
Creating Dashboards
Sharing Dashboards
Tiles in Dashboards
Simple Visualizations
Map Visualizations
Using Excel Data
Importing Excel Files into Power BI
Printing Power BI Dashboards
Publishing Reports to Web
Aggregate Functions
Counting Functions
Logical Functions
Text Functions
Date Functions
Information Functions
DAX Calculation Types
Purchasing
Security
Module 2: Tableau 30 Hours for this Module
+Sorting Data in Visualizations
Sorting and Grouping Data
Filters and Quick Filters
Introduction to Calculated Fields
Creating Basic Calculations
Data Blending
Basic Data Preparation Techniques
Combining Data Sources
Introduction to Geographic Mapping
Plotting Data on Maps
Custom Geocoding
Introduction to Dashboards
Designing Effective Dashboards
Creating Stories in Tableau
Storytelling with Data
Dual-Axis and Combo Charts
Box Plots and Histograms
Introduction to Data Visualization
Tableau Overview and Installation
Connecting to Data Sources
Creating Bar Charts, Line Charts, Scatter Plots, and Pie Charts
Dimensions and Measures
Dimensions vs. Measures
Module 3: MS SQL Server 30 Hours for this Module
+What is SQL Server?
Usage of SQL Server
SQL Server Components
SQL Server Editions and Features
Installation of MS SQL Server
General Architecture
Memory Architecture
Data File Architecture
Log File Architecture
Method 1 – Using SQL Server Management Studio
Method 2 – Using T-SQL Script
System Databases
User Databases
Create, Select, and Drop Database
Method 1 – Using T-SQL Script or Restore Database
Method 2 – Using SQL Server Management Studio
Creating Backups
Restoring Database
Monitoring Database
Creating Users & Assigning Permissions
Method 1 – Using T-SQL Script
Method 2 – Using SQL Server Management Studio
SQL Server
SQL Server Agent
Other Services
Replication
Log Shipping
Database Mirroring
Clustering
AlwaysON Availability Groups
Module 4: Data Science with R 30 Hours for this Module
+Introduction to R and RStudio
Overview of R Programming
Environmental Setup of R
R Packages and Libraries
Basic Data Manipulation in R
Data Formats (Excel, CSV, etc.)
Reading and Writing Data Files
Data Visualization Principles
Creating Bar Charts and Dot Plots
Creating Histograms and Box Plots
Customizing Plots
Introduction to the dplyr Package
Data Filtering, Sorting, and Summarizing
Data Reshaping and Pivoting
Merging and Joining Data
Data Transformation
Computing Basic Statistics
Descriptive Statistics
Data Munging Basics
Comparing Means of Two Samples
Linear Regression
Logistic Regression
Hypothesis Testing
Non-Parametric Tests
Identifying and Handling Missing Data
Reshaping Data
Introduction to Machine Learning
Splitting Data into Training & Testing Sets
Supervised vs. Unsupervised Learning
Linear & Logistic Regression (ML Perspective)
Decision Trees and Random Forests
k-Means Clustering
Evaluation Metrics for Classification and Clustering
Module 5: Data Science with Python 30 Hours for this Module
+-
Types (strings, lists, dictionaries, and more)
-
Control Flow (if-then statements, looping)
-
Organizing Code (functions, modules, packages)
-
Reading and Writing Files
-
Overview of Object-Oriented Programming (OOP)
-
Understanding the N-dimensional Data Structure
-
Creating Arrays
-
Indexing Arrays
-
Array Operations and Manipulations
-
Plotting with Matplotlib
-
Tabular Datasets
-
Data Aggregation & Exploration
-
Labelling Data
-
Handling Missing Values and Time Series
-
Reading and Writing Local Files (.txt, .csv, .xls, .json)
-
Reading Remote Files
-
Web Scraping (.html)
-
Using Read Table Method
-
Pandas Data Structures: Series & DataFrames
-
Indexing, Slicing, Fancy & Boolean Indexing
-
Data Wrangling
-
Adding, Dropping, Selecting, Creating, and Combining Rows & Columns
-
Structure of a Figure
-
Scatter, Line, Box, Bar, Histogram Plots
-
Customizing Plots
-
Split-Apply-Combine with DataFrames
-
Summarization & Aggregation Methods
-
Group By Method
-
Reshaping, Pivoting, and Transforming Data
-
Simple & Rolling Statistics
-
Linear Regression
-
Support Vector Machine (SVM)
-
K-Nearest Neighbors (KNN)
-
Logistic Regression
-
Decision Tree
-
K-Means
-
Random Forest
-
Naive Bayes
-
Dimensional Reduction Algorithms
-
Gradient Boosting Algorithms
-
Autoregressive Integrated Moving Average (ARIMA)
-
Seasonal Autoregressive Integrated Moving-Average (SARIMA)
-
Seasonal ARIMA with Exogenous Regressors (SARIMAX)
Python Basics
NumPy & 2D Plotting Library
Python Pandas & Data Analysis
Accessing Data from Multiple Sources
Data Preparation & Cleaning
Data Visualization
Data Analysis
Python Data Science
Python Forecasting Modeling in Data Science
🎓 What You Will Learn
Practical Knowledge
Learn concepts through real-life examples and hands-on activities designed to strengthen your understanding.
Critical Thinking
Develop the ability to analyze problems, evaluate solutions, and make informed decisions with confidence.
Communication Skills
Improve your written and verbal communication to express ideas clearly and effectively.
Problem Solving
Build logical reasoning and creativity to tackle challenges effectively and independently.
🚀 Upcoming Batches
Hurry up! Limited seats available for our most in-demand courses.
🔥 Filling Fast
Become Career Ready With Us
- Enroll once & get access to all courses.
- Small batch sizes (only 20 seats).
- Internships + 2 Global Certifications.
- Practice on platforms like LeetCode & HackerRank.
- 6-Month On-Job Support & Corporate Visits.
Turn Your Learning Into a Career That You’re Proud Of
01
Follow 3A
Attendance, Assignment & Assessment — your path to structured learning success.
02
Industry Skills
Hands-on practice with tools that match real industry demand.
03
Profile Building
Build a winning resume, LinkedIn profile & web portfolio.
04
Exam
Prove your expertise with our industry-standard evaluation exam.
05
Global Certification
Earn globally recognized certifications to showcase your skills.
06
Internship
Apply what you’ve learned in real-world projects & gain experience.
Instructors
Mentors Behind Your Career Growth
Mr. Sujeet Yadav
Fullstack Teacher
St.Vincent Palloti College of Engineering & Technology, Nagpur.
Mr. Manoj Chowrasiya
Fullstack Teacher
University Department Of Computer Science, University Of Mumbai Kalina Campus.
Mr. Vivek Pal
Fullstack Teacher
University Department Of Computer Science, University Of Mumbai.
Mr. Shibin Alva
Fullstack Teacher
Thakur College of Engineering & Technology,Kandivli.
Mr. Aakash Vishwakarma
Fullstack teacher
Thakur College of Engineering & Technology, Mumbai.
Mr. Uttam Vishwakarma
Fullstack Teacher
Thadomal Shahani College of Engineering, Bandra.
What Our Students Say
Anjali
(College Student)
“TechUpgrad makes learning very simple. I am not from a technical background, so I was worried at first. But the teachers explain slowly and repeat if we don’t understand. They also give practical tasks after every session. This has helped me gain confidence and stop feeling scared of technology.”
Ravi
(Student)
“I never understood coding before. After joining TechUpgrad, I can finally make small programs. The teachers explain very clearly.”
Meera
(Professional)
“Since I already have a full-time job, I wanted something flexible. TechUpgrad was perfect for me because the classes are well-organized, and I could adjust timings when required. The mentors always guided me patiently, even when I struggled. I learned new skills without stress, and it is already helping me at work.”
Parents
(Parents Feedback)
“My daughter is only 11, but TechUpgrad made learning fun for her. The classes are interactive, and the trainers are very friendly with kids. She recently created her first small game, and the smile on her face said it all. I am glad she is learning technology in such a positive way.”
Rahul
(Begginer)
“Earlier I thought coding was very hard. But now I can make small apps. It feels really good to learn with TechUpgrad.”
Meera
(Proffesional)
“I have a job, so I needed flexible timing. TechUpgrad helped me learn without stress. The support is always there.”
Ravi
(Student)
“Before joining TechUpgrad, coding looked very difficult to me. I used to watch online videos but never understood properly. Here, the teachers explain step by step and clear every doubt. Slowly, I started writing my own code. Now I feel proud that I can make small programs on my own.”
Parents
(Parents Feedback)
“My daughter enjoys her TechUpgrad classes. She is just 11 and already made her first small game. I am very happy.”
Rahul
(Begginer)
“Earlier I thought coding was only for very smart people. But after joining TechUpgrad, I realized anyone can learn with the right guidance. The trainers start from basics and give us small projects to practice. After some weeks, I was able to make my own simple app. It gave me a lot of confidence.”
Anjali
(College Student)
“Classes are simple and easy to follow. I don’t feel lost anymore. TechUpgrad makes learning step by step.”
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Maharashtra
Ambernath Branch
Ambernath (Mumbai Metropolitan Region)
Address : Near Ambernath East Railway Station,
Ambernath (E), Mumbai, Maharashtra – 421501
