Mastering in Data Analytics Course in Nellore

Job Oriented Training

Enroll in the Master Data Analytics course at 3RI Technologies in Nellore, known for its excellence in Data Analytics education. Acquire proficiency in data processing tools like Excel, SQL/NoSQL, and visualization tools such as Tableau and Power BI. Develop expertise in database management, data visualization, and advanced Excel techniques to enhance your data skills and productivity. Kickstart your career in Data Analytics with comprehensive training from industry experts.

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Key Features

Course Duration : 5 Months

Live Projects : 4

Online Live Training

EMI Option Available

Certification & Job Assistance

24 x 7 Lifetime Support

Our Industry Expert Trainer

We are a team of 10+ Years of Industry Experienced Trainers, who conduct the training with real-time scenarios.
The Global Certified Trainers are Excellent in knowledge and highly professionals.
The Trainers follow the Project-Based Learning Method in the Interactive sessions.

Data Analyst Course in Nellore


Elevate your career and gain data-driven insights with 3RI Technologies’ Data Analytics training in Nellore .Whether you’re embarking on this exciting journey or seeking to enhance your existing expertise, our meticulously crafted courses equip you with the knowledge and tools to become a master in this highly sought-after domain. 

Learn how to wield data for smarter decision-making, persuasively communicate insights, and develop the quantitative abilities to thrive as an analyst. Begin an enriching journey into the realm of analytics with us.

Start building a brighter future and enroll in our Data Analytics program today.

  1. Key Learning Areas:

Master the Art of Data Analytics with Our Transformative Learning Program

Our comprehensive Data Analyst training is meticulously designed to equip you with in-demand skills to thrive in today’s data-driven world.

 Gain expertise across key modules:

Data Wrangling: Transform raw data into usable insights with cleansing and structuring techniques

Statistical Analysis: Identify trends and patterns through hypothesis testing, regression modelling and forecasting

Data Visualization: Learn to communicate insights clearly through impactful charts and dashboards

Big Data Tools: Harness the power of Hadoop, Spark, Python for large dataset analysis

Real-World Applications: Analyze customer behavior, optimize marketing, predict trends through hands-on case studies

Whether you’re starting out or upskilling as an experienced professional, our program will prepare you for success as an in-demand Data Analyst.

Join our transformative learning journey to master data-driven decision making. Empower your career and drive organizational success through the strategic use of data. Master Data Analytics with our comprehensive programs, unlocking invaluable insights that fuel growth and confidence.


About Data Analytics Course :

Transform Data into Actionable Insights with 3RI Technologies

At 3RI Technologies, our skilled data analysts employ statistical and computational techniques to unlock deep insights hidden within large datasets. We go beyond just collecting big data, transforming it into intelligence that powers better decision-making.

Our rigorous Data Analysis process involves:

  •   Structuring and cleansing raw data to extract relevance
  •   Applying statistical modeling to reveal trends and patterns
  •   Using machine learning algorithms to make predictions and forecasts
  •   Visualizing data insights through compelling interactive dashboards

By uncovering granular details and hidden relationships, we empower organizations to optimize processes, capitalize on opportunities, mitigate risks, and confidently guide strategy.

Collaborate with our team of analytics experts to guide your organization using real-time, data-driven insights. We transform big data into a valuable asset, offering a competitive advantage. Explore the full potential of your Data with 3RI Technologies today.

Why Choose Data Analytics Training?

Unlocking the Power of Data in Nellore

In today’s digital era, organizations in Nellore recognize the strategic value of data analytics. Our Data Analytics training at 3RI Technologies empowers individuals to derive impactful insights from data.

Through our comprehensive curriculum, we equip aspiring data professionals with technical capabilities and business acumen. You will gain hands-on experience with leading analytics tools and tackle real-world case studies. Whether your goal is to be a data analyst, business intelligence expert, or Data Scientist, our program sets the stage for success in these fields.

By developing expertise in harnessing data, you can drive innovation, improve efficiency, and give companies a competitive edge. Join our Nellore  Analytics bootcamp to shape your future and your industry. Our training will provide you with the in-demand data abilities that forward-thinking organizations seek today. Enroll now and position yourself at the forefront of the data-driven world.

Discover the World of Data Analytics with 3RI Technologies:

Master Data Analytics with 3RI Technologies

At 3RI Technologies, our comprehensive Data Analytics training empowers you with in-demand skills to unlock the power of data. Through hands-on learning, you’ll gain practical experience analyzing data, extracting insights, and driving impactful business decisions.

Our expert instructors will lead you through real-world case studies, helping you develop the skills needed to excel as a data professional. We believe in learning by doing. Our interactive training allows you to apply advanced techniques right away, from basic SQL to Python programming and data visualization.

With flexible class schedules and personalized support, we cater to diverse learners – from career changers to seasoned professionals. Our modern facilities and interactive teaching approaches offer an exceptional educational experience.

Start your journey to transformational learning with 3RI Technologies today. Build proficiency in Data Analytics and set yourself up for success in this thriving industry. With customized guidance, you’ll gain the skills needed to unlock data-driven insights and drive success in any industry.

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Data Analytics Course Syllabus

Decade Years Legacy of Excellence | Multiple Cities | Manifold Campuses | Global Career Offers

  1. Fundamentals of Data Science and Machine Learning
  • Introduction to Data Science
  • Need of Data Science
  • BigData and Data Science’
  • Data Science and machine learning
  • Data Science Life Cycle
  • Data Science Platform
  • Data Science Use Cases
  • Skill Required for Data Science
  1. Mathematics For Data Science
  • Linear Algebra
    • Vectors
    • Matrices
  • Optimization
    • Theory Of optimization
    • Gradients Descent
  1. Introduction to Statistics
  • Descriptive vs. Inferential Statistics
  • Types of data
  • Measures of central tendency and dispersion
  • Hypothesis & inferences
  • Hypothesis Testing
  • Confidence Interval
  • Central Limit Theorem
  1. Probability and Probability Distributions
  • Probability Theory
  • Conditional Probability
  • Data Distribution
  • Distribution Functions
    • Normal Distribution
    • Binomial Distribution
  1. Using Spreadsheet
  • What is Excel?
  • Why Use Excel?
  • Excel Overview
  • Excel Ranges,Selection of Ranges
  • Excel Fill,Fill Copies,Fill Sequences,Sequence of Dates
  • Excel add,move,delete cells
  • Excel Formulas
  • Relative and Absolute References
  1. Functions
  • SUM
  • MAX & MIN
  • TRIM
  • LEN
  1. Advanced Functions
  • Excel IF Function
  • Excel If Function with Calculations
  • How to use COUNT, COUNTIF, and COUNTIFS Function?
  • Excel Advanced If Functions
  1. Data Visualization
  • Excel Data Analysis – Data Visualization
  • Visualizing Data with Charts
  • Chart Elements and Chart Styles
  • Data Labels
  • Quick Layout


  • An Introduction to RDBMS & SQL
  • Data Retrieval with SQL
  • Pattern matching with wildcards
  • Basics of sorting
  • Order by clause
  • Aggregate functions
  • Group by clause
  • Having clause
  • Nested queries
  • Inner join
  • Multi join
  • Outer join
  • Adding and Deleting columns
  • Changing column name and Data Type
  • Creating Table from existing Table
  • Changing Constraints Foreign key.
  1. An Introduction to Python
  • Why Python , its Unique Feature and where to use it?
  • Python environment Setup/shell
  • Installing Anaconda
  • Understanding the Jupyter notebook
  • Python Identifiers, Keywords
  • Discussion about installed module s and packages
  1. Conditional Statement ,Loops and File Handling
  • Python Data Types and Variable
  • Condition and Loops in Python
  • Decorators
  • Python Modules & Packages
  • Python Files and Directories manipulations
  • Use various files and directory functions for OS operations
  1. Python Core Objects and Functions
  • Built in modules (Library Functions)
  • Numeric and Math’s Module
  • String/List/Dictionaries/Tuple
  • Complex Data structures in Python
  • Python built in function
  • Python user defined functions

4. Introduction to NumPy

  • Array Operations
  • Arrays Functions
  • Array Mathematics
  • Array Manipulation
  • Array I/O
  • Importing Files with Numpy

5. Data Manipulation with Pandas

  • Data Frames
  • I/O
  • Selection in DFs
  • Retrieving in DFs
  • Applying Functions
  • Reshaping the DFs – Pivot
  • Combining DFs
  • Data Alignment 

6. SciPy

  • Matrices Operations
  • Create matrices
    Inverse, Transpose, Trace,   Norms , Rank etc
  • Matrices Decomposition
  • Eigen Values & vectors
  • SVDs

7.Visualization with Seaborn

    • Seaborn Installation
    • Introduction to Seaborn
    • Basics of Plotting
    • Plots Generation
    • Visualizing the Distribution of a Dataset
    • Selection color palettes  

8. Visualization with Matplotlib

  • Matplotlib Installation
  • Matplotlib Basic Plots & it’s Containers
  • Matplotlib components and properties
  • Pylab & Pyplot
  • Scatter plots
  • 2D Plots-
  • Histograms
  • Bar Graphs
  • Pie Charts
  • Box Plots
  • Customization
  • Store Plots

9. SciKit Learn

  • Basics
  • Data Loading
  • Train/Test Data generation
  • Preprocessing
  • Generate Model
  • Evaluate Models

10. Descriptive Statistics

  • Data understanding
  • Observations, variables, and data matrices
  • Types of variables
  • Measures of Central Tendency
  • Arithmetic Mean / Average
    • Merits & Demerits of Arithmetic Mean and Mode
    • Merits & Demerits of Mode and Median
    • Merits & Demerits of Median Variance

11. Probability Basics

  • Notation and Terminology
  • Unions and Intersections
  • Conditional Probability and Independence

12. Probability Distributions

  • Random Variable
  • Probability Distributions
  • Probability Mass Function
  • Parameters vs. Statistics
  • Binomial Distribution
  • Poisson Distribution
  • Normal Distribution
  • Standard Normal Distribution
  • Central Limit Theorem
  • Cumulative Distribution function

13.  Tests of Hypothesis

  • Large Sample Test
  • Small Sample Test
  • One Sample: Testing Population Mean
  • Hypothesis in One Sample z-test
  • Two Sample: Testing Population Mean
  • One Sample t-test – Two Sample t-test
  • Paired t-test
  • Hypothesis in Paired Samples t-test
  • Chi-Square test

14. Data Analysis

  • Case study- Netflix
  • Deep analysis on Netflix data
  1. Exploratory Data Analysis
  • Data Exploration
  • Missing Value handling
  • Outliers Handling
  • Feature Engineering
  1. Feature Selection
  • Importance of Feature Selection in Machine Learning
  • Filter Methods
  • Wrapper Methods
  • Embedded Methods
  1. Machine Learning: Supervised Algorithms Classification
  • Introduction to Machine Learning
  • Logistic Regression
  • Naïve Bays Algorithm
  • K-Nearest Neighbor Algorithm
  • Decision Tress
    1. SingleTree
    2. Random Forest
  • Support Vector Machines
  • Model Ensemble
  • Model Evaluation and performance
    • K-Fold Cross Validation
    • ROC, AUC etc…
  • Hyper parameter tuning
    • Regression
    • classification
  1. Machine Learning: Regression
  • Simple Linear Regression
  • Multiple Linear Regression
  • Decision Tree and Random Forest Regression
  1. Machine Learning: Unsupervised Learning Algorithms
  • Similarity Measures
  • Cluster Analysis and Similarity Measures
  1. Ensemble algorithms
  • Bagging
  • Boosting
  • Voting
  • Stacking
  • K-means Clustering
  • Hierarchical Clustering
  • Principal Components Analysis
  • Association Rules Mining & Market Basket Analysis

7. Recommendation Systems

  • collaborative filtering model
  • content-based filtering model.
  • Hybrid collaborative system.
  1. Artificial Intelligence
    • An Introduction to Artificial Intelligence
    • History of Artificial Intelligence
    • Future and Market Trends in Artificial Intelligence
    • Intelligent Agents – Perceive-Reason-Act Loop
    • Search and Symbolic Search
    • Constraint-based Reasoning
    • Simple Adversarial Search (Game-Playing)
    • Neural Networks and Perceptions
    • Understanding Feedforward Networks
    • Boltzmann Machines and Autoencoders
    • Exploring Backpropagation
  2. Deep Networks and Structured Knowledge
    • Understanding Sensor Processing
    • Natural Language Processing
    • Studying Neural Elements
    • Convolutional Networks
    • Recurrent Networks
    • Long Short-Term Memory (LSTM) Networks
  3. Natural Language Processing
    • Natural Language Processing
    • Natural Language Processing in Python
    • Studying Deep Learning
    • Artificial Neural Networks
    • ANN Intuition
    • Plan of Attack
    • Studying the Neuron
    • The Activation Function
    • Working of Neural Networks
    • Exploring Gradient Descent
    • Stochastic Gradient Descent
    • Exploring Backpropagation
  4. Artificial and Conventional Neural Network
    • Understanding Artificial Neural Network
    • Building an ANN
    • Building Problem Description
    • Evaluation the ANN
    • Improving the ANN
    • Tuning the ANN
  5. Image Processing / Machine Vision
  • Image basics
  • Loading and saving images
  • Thresholding
  • Bluring
  • Masking
  • Image Augmentation
  1. Conventional Neural Networks
  • CNN Intuition
  • Convolution Operation
  • ReLU Layer
  • Pooling and Flattening
  • Full Connection
  • Softmax and Cross-Entropy
  • Building a CNN
  • Evaluating the CNN
  • Improving the CNN
  • Tuning the CNN
  1. Recurrent Neural Network
  • Recurrent Neural Network
  • RNN Intuition
  • The Vanishing Gradient Problem
  • LSTMs and LSTM Variations
  • Practical Intuition
  • Building an RNN
  • Evaluating the RNN
  • Improving the RNN
  • Tuning the RNN
  1. Time Series Data
  • Introduction to Time series data
  • Data cleaning in time series
  • Pre-Processing Time series Data
  • Predictions in Time Series using ARIMA, Facebook Prophet models.
  1. Introduction to Git& Distributed Version Control
  2. Life Cycle
  3. Create clone & commit Operations
  4. Push & Update Operations
  5. Stash, Move, Rename & Delete Operations.

Machine Learning Features and Services

  • Using python in Cloud
  • How to access Machine Learning Services
  • Lab on accessing Machine learning services
  • Uploading Data
  • Preparation of Data
  • Applying Machine Learning Model
  • Deployment by Publishing Models using AWS or other cloud computing

1.Introduction  to Data Visualization and the Power of Tableau

  • Architecture of Tableau
  • Product Components
  • Working with Metadata and Data Blending
  • Data Connectors
  • Data Model
  • File Types
  • Dimensions & Measures
  • Data Source Filters
  • Creation of Sets

2.Scatter Plot

  •  Gantt Chart
  • Funnel Chart
  • Waterfall Chart
  • Working with Filters
  • Organizing Data and Visual Analytics
  • Working with Mapping
  • Working with Calculations and Expressions
  • Working with Parameters
  • Charts and Graphs
  • Dashboards and Stories
  • Machine Learning end to end Project blueprint
  • Case study on real data after each model.
  • Regression predictive modeling – E-commerce
  • Classification predictive modeling – Binary Classification
  • Case study on Binary Classification – Bank Marketing
  • Case study on Sales Forecasting and market analysis
  • Widespread coverage for each Topic
  • Various Approaches to Solve Data Science Problem
  • Pros and Cons of Various Algorithms and approaches
  • Amazon-Recommender
  • Image Classification
  • Sentiment Analysis

Project Domains: Finance

  • Insurance company wants to decide on the premium using various parameters of the client.
  • It’s an important problem to keep the clients and attract new ones.

By completing this project you will learn:

  • How to collect data?, how to justify right features? , Which ML / DL model is best in this situation? How much data is enough?
  • How to have CI/CD in the project?
  • How to do Deployment of Project to cloud?

Image Processing in Health care

  • A hospital wants to automate Detection of pneumonia in X-rays using image processing.

By doing this project you will understand

  • How to handle image data? How to preprocess and augment image data? How to choose right model for image process?
  • How to apply transfer learning in image processing?
  • How to do incremental learning & CI/CD in the project?
  • How to do Deployment of Project to cloud?

Natural Language Processing

  • One of the companies wants to automate applicant’s level in English communication.
  • Create a ML/DL model for this task.

By completing this project you will learn

  • How to do convert text to right representation? How to preprocess text data? How to select right ML/DL model for text data ?
  • How to do transfer learning in Text Analytics?
  • How to do CI/CD in text analytics project?
  • How to do Deployment of Project to cloud?


  • A mechanical company wants to perform predictive maintenance of engine parts.
  • This enables company to efficiently change parts before machine fails.

By performing this task you will learn,

  • How to handle time series data?
  • How to preprocess time series data?
  • How to create ML/DL model for Time series Data?
  • How to do CI/CD in text analytics project?
  • How to do Deployment of Project to cloud?

Sales / Demand Forecasting

  • Predict the sales / demand of a product of a company.
  • Sales / Demand forecasting of the product will help company efficiently manage the resources.
  • Create a ML/DL model for this problem.

By performing this project you will learn,

  • How to handle time series data?
  • How to preprocess time series data?
  • How to create ML/DL model for Time series Data?
  • How to do CI/CD in text analytics project?
  • How to do Deployment of Project to cloud?

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Industry Projects

Learn through real-life industry projects sponsored by top companies across industries

Dedicated Industry Experts Mentors

Receive 1:1 career counselling sessions & mock interviews with hiring managers. Further your career with our 300+ hiring partners.

Batch Schedule

Schedule Your Batch at your convenient time.

31-Mar-24 | SAT-SUN 8:00 AM to 10:00 AM

15-Apr-24 | MON-FRI 8:00 AM to 10:00 AM

28-Apr-24 | SAT-SUN 8:00 AM to 10:00 AM

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Will I Get Certified?

Upon successfully completing this program, you’ll earn a certificate.

The 3RI certification is accepted and respected by every significant multinational company across the nation. Fresh graduates and corporate trainees are eligible for the assistance. We offer certificate once the academic and practical courses have been finished. The certification that we offer here at 3RI is recognized across the country. The value of your resume will grow as a result. With the assistance of this qualification, you will be able to obtain prominent employment posts in the most successful multinational corporations in the country. The completion of our course as well as the projects that are based on practical application, are prerequisites for receiving the certificate.


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Data Analytics Training In Nellore

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Frequently Asked Questions

1.What resources or materials will be provided to support learning?

3RI Technologies offers a range of resources to support learning, such as comprehensive course materials, software access, hands-on projects, and guidance from experienced instructors. These resources enhance the learning experience, ensuring students gain the skills needed for success in Data Analytics.

2. Are there opportunities for hands-on experience or real-world projects?

Yes, the Data Analytics course at 3RI Technologies offers extensive opportunities for hands-on experience and real-world projects. Students work on practical assignments and case studies, allowing them to apply their skills in real-world scenarios and enhance their learning experience.

3. Is there any career support or job placement assistance provided?

Yes, 3RI Technologies offers extensive career support and job placement assistance to facilitate a smooth transition for students entering the workforce. From resume building to interview preparation, we offer valuable guidance and resources to maximize career opportunities in Data Analytics.

4. How will my progress be assessed throughout the course?

Your progress in the Data Analytics course at 3RI Technologies will be assessed through a combination of exams, projects, and practical assignments, ensuring a comprehensive evaluation of your skills and understanding.

5. How do I enroll in the course, and what is the process for enrolling?

To enroll in our data analytics course at 3RI Technologies, simply visit our website and fill out the online enrollment form. Our admissions team will guide you through the process.

6. What is the course fee, and are there any payment plans?

The fee structure for the Data Analytics course at 3RI Technologies varies depending on factors such as course duration and mode of delivery. We offer flexible payment plans to accommodate different financial situations.

7. What is the course curriculum, and does it cover both basic and advanced topics?

The Data Analytics course at 3RI Technologies covers a wide range of topics, including basic concepts such as data analysis and visualization, as well as advanced topics like machine learning and predictive analytics. The curriculum is designed to provide a comprehensive understanding of Data Analytics.

8.What is the duration of the Data Analytics Course ?

The duration of our data analytics course typically spans between 5 to 6 months, depending on the specific program chosen by the individual. 

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