Mastering in Data Analytics Course in Raipur

Job Oriented Training

Delve into the Realm of Data Analytics with 3RI Technologies!Make informed decisions, gain valuable insights, and advance your career with our comprehensive Data Analytics training.Our courses are designed for all levels, ensuring success in this dynamic field. Start your path to becoming a skilled Data Analyst in Raipur by enrolling today.

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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 [Location]

Overview

Explore the Depths of Data with 3RI’s Dynamic Program in Raipur.Embark on an enriching learning journey in Data Analytics with 3RI Technologies in Raipur. Our comprehensive program is carefully crafted to equip you with the essential skills and knowledge needed to excel in the dynamic field of Data Analytics.

Our curriculum strikes a perfect balance between theoretical foundations and practical applications. By participating in interactive projects and analyzing real-world case studies, you’ll develop a profound comprehension of Data Analytics techniques and tools. Discover how Data Analytics empowers businesses to drive success and innovation, even in the dynamic city of Raipur.

Key Learning Areas:

Start a transformative learning journey to become a master of Data Analytics.Our comprehensive program is meticulously crafted to equip you with the skills and knowledge to thrive in the ever-evolving landscape of data-driven decision-making.

Core Modules:

Data Collection and Cleansing: Gather, prepare, and structure raw data effectively.

Statistical Analysis and Modeling: Employ hypothesis testing, regression analysis, and forecasting techniques to analyze data effectively.

Data Visualization: Communicate insights clearly and persuasively through compelling charts and dashboards.

Big Data Technologies: Delve into industry-leading tools like Hadoop, Spark, and Python libraries to handle large datasets.

Practical Projects and Real-World Applications:

Put your knowledge into practice with engaging projects and real-world case studies. Gain confidence in analyzing customer behavior, optimizing marketing strategies, predicting market trends, and making strategic decisions.

Career Advancement:

Our Data Analyst training program is tailored for both beginners and experienced professionals seeking to excel in the high-demand field of Data Analytics. Join us to become a skilled data analyst, equipped to harness the power of data and drive business success. Empower your career and organization with insights fueled by data.

 

What is Data Analytics?

Data analytics is a complex process involving the careful analysis of large datasets to uncover detailed patterns and insights crucial for making strategic decisions. At 3RI Technologies, our data analysts are skilled in using statistical and computational techniques to transform raw data into actionable intelligence. This empowers organizations to improve processes, discover opportunities, and manage risks more effectively.

 Unleashing the Potential of Data Analysis: Transitioning from Big Data to Actionable Insights.

Data analytics involves extracting hidden patterns and actionable insights from vast datasets. Using statistical and computational techniques, data analysts at 3RI Technologies unleash the full potential of raw data, turning it into valuable intelligence that informs decision-making. Join us to master the art and science of data analytics, empowering yourself to optimize processes, identify opportunities, mitigate risks, and drive data-driven decisions within your organization.

Why Seek Data Analytics Training?

 In the rapidly evolving digital era, data is being generated at an unprecedented pace across diverse industries. Forward-thinking organizations recognize the crucial role of Data Analytics in gaining a competitive advantage, improving operational efficiency, and driving innovation.

At 3RI Technologies, our Data Analytics training equips individuals with a wide range of skills and specialized expertise needed to harness the transformative power of data, even in Raipur. Whether you aspire to become a skilled Data Analyst, a proficient Business Intelligence professional, or an innovative Data Scientist, our carefully crafted program lays the groundwork for success in these pivotal roles and beyond.

Shape Your Future, Shape Your Industry: Gain a Competitive Edge with Data Expertise.
In today’s data-centric environment, organizations worldwide highly value Data Analytics for its profound impact. By enrolling in our training program, you will develop the skills to effectively leverage data, positioning yourself for success in this dynamic field. Whether you are pursuing a career as a Data Analyst, a Business Intelligence expert, or a Data Scientist, our program provides the essential foundation for excellence and career advancement.

Discover the World of Data Analytics with 3RI Technologies:

Experience the power of Data Analytics with 3RI Technologies. Our extensive training program spans from foundational concepts to advanced techniques, ensuring you are equipped with the skills necessary to excel in this dynamic field. With hands-on experience and expert guidance, you’ll learn how to analyze data, extract valuable insights, and make informed decisions that drive business success.

 At 3RI Technologies, we advocate experiential learning. Our training emphasizes practical, hands-on experience, allowing you to apply theoretical knowledge in real-world situations. Our expert instructors will guide you every step of the way, ensuring you have the support you need to succeed.

 Join us at 3RI Technologies and start your journey towards transformative learning, customized to fit your unique needs and aspirations. Our dedication to excellence shines through in our cutting-edge facilities, seasoned instructors, and interactive learning methods, guaranteeing you an outstanding educational experience. With flexible scheduling and personalized guidance, we cater to a diverse range of learners, from seasoned professionals to recent graduates. Whether you’re aiming to enhance your current skills, acquire new ones, or transition into a new career in Data Analytics, 3RI Technologies equips you with the resources and support necessary to achieve your goals.

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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
  • AVERAGE
  • COUNT
  • MAX & MIN
  • RANDBETWEEN
  • TRIM
  • LEN
  • CONCATENATE
  • TODAY & NOW
  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
    Merge
    Join
  • 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?

Mechanical

  • 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 Raipur Testimonials

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Frequently Asked Questions

1.Does the course offer any certification upon completion, and is it recognized in the industry?

Yes, After completion, the course  provides a certification that is widely recognized in the industry. This certification boosts your credibility and enhances your employability in the field of Data Analytics.

2. How can I get more information or clarify any doubts about the Data Analytics course before enrolling?

You can contact 3RI Technologies directly through Our website or by phone to get more information or clarify any doubts about the course before enrolling.

3. Are there any opportunities for hands-on projects or real-world applications during the Data Analytics classes?

Yes, the Data Analytics classes at 3RI Technologies include opportunities for hands-on projects and real-world applications. These practical exercises enrich your learning experience and reinforce key concepts.

This course incorporates the latest trends and advancements in the field of Data Analytics. Through updated curriculum and access to resources, you’ll stay current with emerging technologies and techniques, ensuring you’re well-equipped to adapt to the evolving landscape of Data Analytics.

5. Does the Data Analytics course cover both foundational and advanced concepts in data Analysis?

Yes, The Data Analytics course covers both foundational concepts, such as data cleaning and basic statistical analysis, and advanced concepts, such as machine learning algorithms and data visualization techniques.

6. Will I have access to any additional resources or support during the Data Analytic classes?

Yes, you will have access to additional resources and support during the classes, such as online materials, discussion forums, and instructor assistance, to enhance your learning experience and understanding of the subject.

7. Can I access course materials and lectures after completing the Data Analytics course for future reference?

Yes, after completing the course, you usually have continued access to course materials and lectures for future reference. This allows you to revisit concepts, review content, and stay updated with the course material, enhancing your understanding and application of Data Analytics principles.

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

The course will assess your progress through a blend of assignments, quizzes, exams, and hands-on projects. These assessments are intended to evaluate how well you understand and apply the course material.

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