Comprehensive Data Analytics Program

Master Data-Driven Decision Making

This Comprehensive Data Analytics Program by Emerging India Analytics is a career-oriented and industry-aligned training course that provides in-depth knowledge and hands-on experience in Data Science, Analytics, and Business Intelligence. Designed for fresh graduates, working professionals, and individuals looking to transition into the data domain, this program helps learners build a strong foundation in Data Handling, Statistical Analysis, Machine Learning, Data Visualization, and real-world project implementation. With expert mentorship, live sessions, and structured learning, participants will gain the essential skills to analyze data, generate insights, and make data-driven decisions.

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Introduction

Comprehensive Data Analytics Program

This 110-hours Comprehensive Data Analytics Program is an intensive, module-based course designed to build strong foundations in Python programming, Statistical Concepts, Machine Learning, Deep Learning, SQL, and Business Intelligence tools such as Tableau and Power BI. The curriculum follows a day-wise structure that simplifies complex topics and supports steady, progressive learning. Participants will work on multiple mini and major projects, gaining practical experience in applying data analytics techniques to real-world challenges. In addition to technical proficiency, the program emphasizes hands-on implementation, ensuring learners are job-ready and confident in using industry-standard tools and frameworks. Upon successful completion, learners receive an industry-recognized certificate, validating their expertise in Data Analytics and Business Intelligence.

Data Science & AI Training

Tools

Python
NumPy
Pandas
Scikit-learn
Tensorflow
Keras
Matplotlib
Seaborn
SQL
Tableau
PowerBI

Program Structure

30-Hours Pre-Learning Module

Before you embark on the live academic session, get ready for the Program. You will get a series of online recorded tutorials to understand the structure of Data Science to know about the fundamentals, which would enrich your future learning experience.

110-Hours Live Instructor-Led Program Training

You will get hands-on experience in SQL, Python, Statistics, Machine Learning, Deep Learning, Tableau, and Power BI through real-time projects, enhancing your practical skills and preparing you for industry roles.

Access to Recorded Live Videos

Learning does not stop here. To support better understanding of concepts and skill mastery, recorded videos of live classes will be provided to learners. These videos will be accessible for up to 6 months after course completion.

Specialized Projects & Assignments

To master the skills acquired during the course, learners are required to complete and submit a few projects within one month of course completion. Expert trainers will be available during this period to provide guidance, support, and clarification when needed.

Curriculum

LEARN WITH A WORLD CLASS CURRICULUM

Module 1. Course Introduction
Day 01: Introduction to Data Science & Analytics
  • Introduction to Data Science
  • Scope of Data Science
  • Data Science methodology
  • Industry applications
Module 2. Python For Data Science
Day 02: Introduction to Python, Why Python, Variables, Operators, Strings, Indexing
  • Python fundamentals
  • Variables and data types
  • Basic operators
  • String manipulation and indexing
Day 03: Data Structures, Functions, Creating Function, Calling a function, Function Parameter
  • Lists, dictionaries, tuples, and sets
  • Function definition and calling
  • Function parameters and return values
  • Function scope
Day 04: Lambda Function, Conditional Statement, Loops and it's Control Statement
  • Lambda functions
  • Conditional statements (if, elif, else)
  • Loops (for, while)
  • Loop control statements (break, continue, pass)
Day 05: NumPy, Pandas for Data Handling
  • NumPy arrays and operations
  • Pandas DataFrames and Series
  • Data manipulation with Pandas
  • Data cleaning and preprocessing
Day 06: Matplotlib, Seaborn for Data Visualization
  • Basic plotting with Matplotlib
  • Advanced visualizations with Seaborn
  • Customizing plots
  • Creating interactive visualizations
Module 3. Statistics For Data Science
Day 07: Introduction to Statistics, Descriptive Statistics, Sample, Population, Major of Central Tendency
  • Fundamentals of statistics
  • Descriptive statistics
  • Population vs. sample
  • Measures of central tendency (mean, median, mode)
Day 08: Standard Deviation, Variance, Range, IQR, Outliers, Correlation, Covariance Skewness, Kurtosis
  • Measures of dispersion
  • Interquartile range and outlier detection
  • Correlation and covariance
  • Distribution characteristics (skewness, kurtosis)
Day 09: Probability, Probability distributions, Central Limit Theorem, Binomial & Normal Distribution
  • Basic probability concepts
  • Common probability distributions
  • Central Limit Theorem
  • Binomial and normal distributions
Day 10: Type I & Type II Error, T-test, Z-test, Hypothesis Testing
  • Hypothesis testing fundamentals
  • Type I and Type II errors
  • T-tests and z-tests
  • Practical applications of hypothesis testing
Module 4. Mini Project
Day 11: Data Analysis & Visualization
  • Exploratory data analysis
  • Data visualization techniques
  • Insight extraction from data
  • Mini project implementation
Module 5. Machine Learning
Day 12: Introduction to ML, Types of variables, Encoding, Normalization, Standardization
  • Machine learning fundamentals
  • Feature types and encoding techniques
  • Data normalization and standardization
  • Preparing data for ML algorithms
Day 13: Linear Regression, Logistic Regression, SVM, KNN
  • Linear regression models
  • Logistic regression for classification
  • Support Vector Machines
  • K-Nearest Neighbors algorithm
Day 14: Naive Bayes, Decision Tree, Random Forest, MSE, RMSE
  • Naive Bayes classifiers
  • Decision trees
  • Random Forest ensemble method
  • Regression metrics (MSE, RMSE)
Day 15: R2 Score, F1-Score, Confusion Matrix, Classification Report, Accuracy
  • Regression evaluation metrics
  • Classification evaluation metrics
  • Confusion matrix analysis
  • Model performance assessment
Day 16: Ensemble Techniques, Xgboost, Unsupervised Machine Learning Introduction
  • Ensemble learning techniques
  • Gradient boosting with XGBoost
  • Unsupervised learning concepts
  • Applications of unsupervised learning
Day 17: PCA, Clustering, k-Means Clustering and Hierarchical clustering
  • Principal Component Analysis
  • Clustering fundamentals
  • K-means clustering
  • Hierarchical clustering
Module 6. Deep Learning
Day 18: Introduction to Neural Network, Forward Propagation, Activation Function (Linear, Sigmoid)
  • Neural network fundamentals
  • Forward propagation process
  • Linear activation function
  • Sigmoid activation function
Day 19: Activation Function (Relu, Leaky Relu), Optimizers, GD, Stochastics Gradient Descent
  • ReLU and Leaky ReLU activation functions
  • Optimization algorithms
  • Gradient Descent
  • Stochastic Gradient Descent
Day 20: Mini batch Gradient Descent, Adagrad, Padding, Pooling, Convolution
  • Mini-batch gradient descent
  • Adaptive gradient algorithm (Adagrad)
  • Convolutional neural networks concepts
  • Padding and pooling operations
Day 21: Checkpoints and Neural Networks Implementation
  • Model checkpointing
  • Practical neural network implementation
  • Deep learning frameworks
  • Training and evaluation processes
Day 22: Time Series Analysis-Introduction, Various components of the TSA
  • Time series concepts
  • Time series components (trend, seasonality, residuals)
  • Time series visualization
  • Stationarity and tests
Day 23: Decomposition Method(Additive and Multiplicative), ARMA, ARIMA
  • Time series decomposition methods
  • Autoregressive Moving Average (ARMA) models
  • Autoregressive Integrated Moving Average (ARIMA) models
  • Forecasting techniques
Module 7. Major Project
Day 24: Machine Learning, & Deep Learning - based Predictive Modeling
  • Predictive modeling techniques
  • Integrating ML and DL approaches
  • Project implementation methodology
  • Model deployment considerations
Module 8. SQL
Day 25: Basic of Database & its Types, Data Types, Operators, Create and Insert
  • Database fundamentals
  • SQL data types
  • SQL operators
  • CREATE and INSERT statements
Day 26: Drop, Truncate, Delete, Alter, Update, Select, Range, Operator, In,Wildcard
  • Data manipulation commands
  • Data definition language (DDL)
  • SELECT statements and filtering
  • Wildcard operators
Day 27: Like, Clause, Constraint, Aggregation Function, Group by, Order by
  • LIKE operator and pattern matching
  • SQL constraints
  • Aggregation functions (SUM, AVG, COUNT, etc.)
  • GROUP BY and ORDER BY clauses
Day 28: Having, Joins, Case, Complex Queries, Doubt Clearing
  • HAVING clause
  • SQL JOINs (INNER, LEFT, RIGHT, FULL)
  • CASE statements
  • Advanced SQL queries
Module 9. Tableau
Day 29: Tableau Desktop, Tableau products
  • Tableau Desktop introduction
  • Tableau product ecosystem
  • Tableau interface navigation
  • Connecting to data sources
Day 30: Data import, Measures, Filters
  • Data importing techniques
  • Dimensions and measures
  • Filter types and applications
  • Data preparation in Tableau
Day 31: Data transformation, Marks, Dual Axis
  • Data transformation options
  • Using marks in visualizations
  • Dual axis charts
  • Advanced visualization techniques
Day 32: Manage worksheets, Data visualization, Dashboards
  • Worksheet management
  • Creating effective visualizations
  • Dashboard design principles
  • Interactive dashboard creation
Module 10. Power BI
Day 33: Power BI Platform, Process Flow
  • Power BI ecosystem
  • Power BI Desktop interface
  • Data workflow in Power BI
  • Connecting to data sources
Day 34: Features, Dataset, and Bias
  • Power BI key features
  • Dataset creation and management
  • Understanding data bias
  • Data preparation techniques
Day 35: Pivoting, Query Group, DAX Function
  • Data pivoting operations
  • Query organization
  • DAX function fundamentals
  • Creating calculated measures
Day 36: Formula, Charts, Reports and Dashboards
  • DAX formulas and expressions
  • Chart types and selection
  • Report creation best practices
  • Dashboard design and deployment
Module 11. Major Project
Day 37: Database to Dashboard: Project Implementation with SQL, Tableau & Power BI
  • End-to-end business intelligence project
  • Database design and implementation
  • Data visualization with Tableau and Power BI
  • Creating interactive business dashboards
Module 12. Real World Projects
Day 38: Machine Learning, & Deep Learning - based Predictive Modeling
  • Predictive modeling techniques
  • Integrating ML and DL approaches
  • Project implementation methodology
  • Model deployment considerations

Skills You Will Possess

Data Manipulation
Data Wrangling
Data Cleaning
Data Visualization
Data Analysis
Descriptive Analytics
Machine Learning
Predictive Analytics
Text Processing

Program Benefits

Cutting Edge Curriculum

Hand crafted Course content made by Experts from various Industries. Learn through Practical case studies and multiple projects.

On the Go Learning

Online accessible E-learning Material, live interactive lectures, Industrial Graded Projects, Case Studies and Multiple Tests & Evaluations.

Build Solid Foundation

You will get 110 hours of live instructor-led lectures on the most in-demand Data Science tools.

Industry Mentorship

Receive one-on-one guidance from industry experts and confidently begin your career in the field of Data Science.

Recognized Certification

Earn a Government of India approved & globally recognized certificate by NASSCOM IT- ITes SSC by clearing assessment Exam.

Industry Certificate

Opportunity to earn Highest Industry Certificate of Senior Associate Analytics (NSQF LEVEL 5) from SSC NASSCOM.

Course Certificates

Upon successful completion of the program and passing the final assessment, you will receive:

  • Course Completion Certificate from Emerging India Analytics
  • NASSCOM IT-ITeS Sector Skill Council Certification
  • Opportunity to earn Senior Associate Analytics (NSQF LEVEL 5) certification from SSC NASSCOM

These certifications are recognized by employers globally and validate your expertise in Data Science and AI.

Sample Certificate
Sample Certificate

Real World Projects

Projects will be a part of your Comprehensive Data Analytics Program to solidify your learning. They ensure you have real-world experience in Data Science and AI.

Practice 20+ Essential Tools

Designed by Industry Experts

Get Real-world Experience

Beginner

Real Estate Analytics

Real Estate Analytics uses supervised learning with ensemble regression algorithms to predict outcomes and minimize errors by optimizing model parameters for improved accuracy and better performance.

Intermediate

Solar Power Efficiency

The project will encompass three target variables that we will predict using the supervised machine learning algorithms for regression problems and minimize the error by tuning the hyperparameters.

Advanced

Recommendation Engine

In the Recommendation Engine project, we will use singular value decomposition to draw out relevant recommendations for music and movie selections based on the historical data points.

Career Services By emergingindiagroup

Soft Skills

Learners will be closely mentored to develop key soft skills like communication, teamwork, and adaptability, enhancing their career path.

Interview Preparation

Participate in mock interviews and receive detailed feedback sessions with experienced industry experts.

Profile Building

Attend resume workshops and get your LinkedIn profile optimized for better professional visibility.

Placement Assistance

Placement opportunities become available upon clearing the Placement Readiness Test and meeting eligibility criteria.

Exclusive access

Get exclusive access to our dedicated job portal to apply for open positions. Partnering with a select few start-ups and product companies, we offer personalized mentorship and support to help you explore relevant job opportunities and advance your career.

Real World Projects

Projects will be a part of your Comprehensive Data Analytics Program to solidify your learning. They ensure you have real-world experience in Data Analytics Program.

  • Practice 20+ Essential Tools
  • Designed by Industry Experts
  • Get Real-world Experience

Our Alumni Works At

Learners thought about us

"
It was a great experience with Emerging India Analytics. The course format and content was very good. The faculty, Ms Lakshmi is very knowledgeable. She know the subject very well and the way she conducted the sessions was very much satisfactory. Thank you so much for your services and wish you all the best. God Bless.
Yogesh Ranjan Ghavnalkar

Yogesh Ranjan Ghavnalkar

Learner

"
As a non-IT background student, I am very much satisfied with the live sessions/classes conducted by Emerging India Analytics. Special thanks to the instructor/trainer, the way he is teaching, from the basic fundamentals, that a student having zero knowledge in IT/CS & coding, can easily understand the subjects/topics.
Tushar Kanta Behera

Tushar Kanta Behera

Learner

"
Classes are progressing smoothly, doubts are consistently addressed, fostering a clear understanding. Positive atmosphere, engaged learning, and effective communication contribute to a successful academic experience.
Aadi Bhardwaj

Aadi Bhardwaj

Learner

"
Coming from non-IT background was initially worrisome but I took the bold step into this course. The tutors have been fantastic as well as the personal support team. Looking back at the journey so far, I will say it's worth the all-round commitment and I recommend this program without reservation.
Israel Samuel

Israel Samuel

Learner

Admission Details

The application process consists of three simple steps. An offer of admission will be made to selected candidates based on the feedback from the interview panel. The selected candidates will be notified over email and phone, and they can block their seats through the payment of the admission fee.

1

Submit Application

Tell us a bit about yourself and why you want to join this program

2

Application Review

An admission panel will shortlist candidates based on their application

3

Admission

Selected candidates will be notified of admission status within one week after review.

Program Fees

Our Loan Partners

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Zero Cost EMI options Available

from RBI Approved NBFCs

Starting from
₹4,999*
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Others Payment Options

We provide the following options for one-time payment.

Internet Banking

Credit / Debit Card

Total Admission Fees
₹42,500*
Apply Now

FAQs

1. What is the duration of the Comprehensive Data Analytics Program?
The Comprehensive Data Analytics Program is a comprehensive 4.5-month course designed to cover a wide spectrum of Data Analytics concepts and tools.
2. What topics are covered in the course?
The course covers a wide range of topics including Python, Statistics, SQL, Tableau, Power BI, Machine Learning, and Deep Learning.
3. Do I need any prior knowledge to enroll in this course?
No prior knowledge is required. The course is designed for both beginners and professionals, starting with foundational concepts and gradually progressing to advanced topics.
4. How are the classes conducted?
Classes are conducted through live interactive sessions led by experienced instructors. Recorded sessions are also provided for flexible learning and future reference.
5. Are there any hands-on projects included in the course?
Yes, the course includes real-world projects designed to ensure practical learning. These hands-on projects help reinforce your understanding and build industry-relevant experience.
6. Will I receive a certificate upon completion?
Yes, upon successful completion of the course and clearing the online exam, you will receive a NASSCOM certification, which is highly recognized across the industry.
7. What kind of support is available if I have questions or need help?
You'll have access to dedicated doubt-clearing sessions, project-based classes, and a responsive support team to assist you with any queries or technical issues throughout the course.
8. Will I receive a certificate upon completion?
Yes, upon successful completion of the course and clearing the online exam, you will receive a NASSCOM certification, which is highly recognized across the industry.
9. Can I try a demo class before enrolling?
Yes, you can request a demo class to experience the teaching methodology and course structure before making a decision.
10. What if I miss a live class?
Don't worry — every live session is recorded and made available to you, so you can review it at your convenience and stay on track.