Advanced Certification Training Program in Data Science & AI

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Advanced Certification in Data Science & AI

Join our Advanced Certification in Data Science & AI, offered in collaboration with E&ICT Academy, IIT Guwahati. This comprehensive program covers essential tools and technologies such as Python Programming, Stats, Maths, SQL, Machine Learning, Natural Language Processing, Deep Learning, TensorFlow, and data visualization techniques. Enhance your data science and AI skills with expert guidance from Ethan’s & E&ICT Academy, IIT Guwahati faculties. With our course, you’ll gain the expertise to handle real-world business situations using a variety of data science and AI tools. Enroll in our Advanced Certification in Data Science & AI today and kickstart your journey to becoming a proficient data scientist.

Student workload: 700 Hours | Duration: 6 months | Training Mode: Classroom 

Register to confirm your seat. Limited seats are available.

About the Course

E&ICT Academy, IIT Guwahati Advanced Certification in Data Science & AI

What is Data Science & AI all about?

Data Science and AI encompass the study and application of advanced techniques to extract valuable insights, automate processes, and make data-driven decisions. Data Science combines statistical methods, programming skills, and domain expertise to analyze and interpret complex data sets. AI, or Artificial Intelligence, focuses on creating systems that can perform tasks typically requiring human intelligence, such as learning, reasoning, and problem-solving.

Key aspects of Data Science and AI include:

  • Data Collection: Gathering extensive and diverse data from various sources like databases, sensors, and social media.
  • Data Cleaning: Ensuring data quality by removing inaccuracies, inconsistencies, and duplicates.
  • Data Processing: Structuring and organizing data to make it suitable for analysis and model training.
  • Exploratory Data Analysis (EDA): Using statistical tools to explore data sets and uncover initial patterns, anomalies, and relationships.
  • Machine Learning: Developing algorithms that enable computers to learn from data and improve their performance over time without being explicitly programmed.
  • Deep Learning: Utilizing neural networks to model complex patterns and achieve state-of-the-art performance in tasks such as image and speech recognition.
  • Data Visualization: Presenting data and analysis results through visual formats like charts, graphs, and dashboards to enhance comprehension.
  • AI Applications: Implementing AI solutions in areas like natural language processing, computer vision, robotics, and predictive analytics to automate tasks and solve complex problems.
  • Interpretation and Decision-Making: Leveraging data-driven insights to inform strategies, optimize operations, and drive innovation across various industries, including healthcare, finance, marketing, and more.

Who is a Data Scientist?

Who is Data Scientist? A Data Scientist is a professional who works extensively with raw, structured, and unstructured data to derive valuable business insights from it. A data scientist uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from many structural and unstructured data.

A Data Scientist enhances business decision making by introducing greater speed and better direction to the entire process with the help of their data visualization capabilities. Compared to data analysts, data scientists are much more technical and possess expertise in at least one programming language – R/Python, data extraction, data wrangling, data transformation, and loading capabilities.

Top Data Science Jobs for the year 2020 compiles of Data Scientist, Machine Learning Engineer, Machine Learning Scientist, Artificial Intelligence, Data Architect, Data Engineer, Data Analyst with an average of INR 700,000 salary.

Why one should take Data Science Course?

“The job of a data scientist has only grown sexier,” said Andrew Flowers, an economist at Indeed, based in Austin, Texas. “More employers than ever are looking to hire data scientists.”

With the surge in data (Calling Big Data) and its correlated fields, the job of a Data Scientist has become the most sought after job. To handle vast amounts of data produced every day, enterprises need professionals who can treat, analyze, and organize this data to provide valuable business insights, for intelligent actions. Data Science has emerged as the most promising field in recent times.

 The demand for data scientists is only increasing and will continue to increase in the future. According to IBM, an increment between 200,000 to 600,000 openings will be generated in the year 2020. This demand will only grow further to an astonishing 700,000 openings.

According to Glassdoor, Data Scientist is the number one job on its website. This position will remain unchanged in the future. The requirement for the number of data scientists is growing at an exponential rate due to the increase in data and its various types. The number of roles and data scientists will only increase in the future. Some of the positions in data science such as data engineer, data science manager & big data architect. Moreover, the financial, telecom, retail, and insurance industries are becoming major players for recruiting data scientists.

The January report from Indeed, one of the top job sites, showed a 29% increase in demand for data scientists year over year and a 344% increase since 2013 — a dramatic upswing. But while demand — in the form of job postings — continues to rise sharply, searches by job seekers skilled in data science grew at a slower pace (14%), suggesting a gap between supply and demand and the site considers data science a “high-demand skill.”.

Accessibility of the data today can help organizations to reap multiple benefits from it. Because of this, companies are not shying away from offering increased data scientist salary in India. Companies are offering huge salaries at those having skills to take on the positions of Data Analysts, Scientists, Engineers, etc. India is the second-highest country to recruit employees in the field of data science or data analytics, etc. with 50,000 positions available – second only to the United States.

What is the scope of Job Opportunities With Data Science Training?

Career opportunities in data have exponentially grown in the recent few years. India is the second-highest country to recruit employees in the field of data science or data analytics, etc. with 50,000 positions available.

If you have completed the certification course in data science from EthansTech, your career as a data scientist is expected to grow onwards and upwards.

The different job roles in Data Science which you can apply after the completion of your Data Science training certification are

  • Data Scientist– Gathering vast amounts of structured and unstructured data and converting them into actionable insights. An encouraging data-driven approach to solving complex business problems.

Average salary:  Rs 7,00,000 per annum

  • Data Engineer- The primary job of a Data Engineer is to design and engineer a reliable infrastructure for transforming data into such formats as can be used by Data Scientists. In an organization, the position of a Data Engineer is as vital as that of a Data Scientist.

Average Salary:  Rs 1,000,000 per annum

  • Data Analyst- Data Analysts are professionals who translate numbers, statistics, figures, into plain English for everyone to understand.

Average Salary:  Rs 6,00,000 per annum

By completing the Certification Course with EthansTech you may likely receive an annual bump up of around 15% in your compensation. This will further increase with an increase in the years of work experience and the number of skills you’ve mastered.

Why Choose Ethans for Data Science ?

This Data Science Training In Pune is an ideal choice for all the analytics career enthusiasts who are planning to secure their careers in Data Science. As the course complements the present industry requirements, both fresher’s & working professionals who are looking towards a career shift from their existing technologies to Data Science can get enrolled for our Data Science Course In Pune. If you are new to programming & stats then there’s nothing to worry about, we have got you covered. Our Data Science training will cover the concepts right from the scratch. You will learn the basics of Statistics, Maths, SQL, EDA, Statistical analysis, Python programming to advanced AI, Machine Learning, Business Analytics & Predictive Analytics, Text Analytics and more.

Our Data Science training is the best fit for

  • Freshers/Graduates
  • Job Seeker
  • Data analysts
  • Business analysts
  • Database Administrators
  • Networking Operators
  • Professional whats to change their career path
  • Legacy Technologies Professional
  • IT Developers & Software Professionals
  • Job Seekers
  • End users


With the increasing demand for big data analytics, Data Science has become the key technology & the major buzz word across the IT & Corporate domain. So, this is the right time to step into this technology. Throughout this Data Science Training In Pune program, our expert trainers & mentors will be extending their full support to the participants. With a coordinated effort in our Data Science Training, we will be working towards transforming our students into complete career ready Data Scientists


E&ICT Academy, IIT Guwahati Advanced Certification in Data Science & AI

Syllabus for Advanced Certification in Data Science & AI at Ethans + E&ICT, IIT Guwahati

Introduction to Computer Programming (Python)

  • Programming Foundation Concepts: Basic Terminology, Data Types and Variables, Operators and Expressions, Control Structures, Functions and Procedures, Recursion, Basic Algorithms
  • Object-Oriented Concepts: Classes and Objects, Inheritance, Polymorphism, Encapsulation, Abstraction, Method Overriding, Constructor and Destructor
  • Getting Started with Python: History of Python, Python Features, Python 2 vs Python 3, Installing Python, Running Python Scripts, Python Syntax and Semantics, Python Development Environments
  • Python Installation and Setup: Python 3.X Installation Guide, Introduction to Anaconda Python, IDEs: Jupyter Notebook, PyCharm, and VS Code, Setting Up Virtual Environments, Package Management with pip and conda
  • Python Built-in Objects: Numbers (int, float, complex), Strings, Lists, Tuples, Sets, Dictionaries, Type Conversion
  • Control Flow in Python: Conditional Statements (if, elif, else), Looping Statements (for, while), Nested Loops, Loop Control Statements (break, continue, pass), Comprehensions (List, Dict, Set), Conditional Expressions
  • Functions in Python: User Defined Functions, Lambda Functions, Function Arguments (default, keyword, arbitrary), Return Statement, Recursion, Built-in Functions, Higher-Order Functions
  • String Handling in Python: String Creation and Operations, String Methods, String Formatting, Regular Expressions, String Slicing, Escape Characters, Unicode Strings
  • Data Structures in Python: List Operations and Methods, Dictionary Operations and Methods, Set Operations and Methods, Tuple Operations and Methods, Working with Stacks and Queues, Comprehensions, Collections Module
  • File Handling in Python: Reading and Writing Files, File Methods, File Modes, Handling Binary Files, Working with CSV Files, Context Managers, File Path Operations
  • Python Libraries and Modules: Standard Library Overview, Commonly Used Libraries (os, sys, math, datetime), Importing Modules, Creating User Defined Modules, User Defined Packages, Working with, Packaging and Distribution (whl Packaging)
  • Advanced Python Concepts: Object Oriented Python, Exception Handling, Debugging Techniques, Iterators and Generators, Decorators, Context Managers, Metaprogramming
  • Database Interface with Python: Introduction to Databases, SQLite in Python, CRUD Operations, Connecting to Sqlite, Database Connection Pooling, Handling Transactions
  • Working with Data Formats: Introduction to JSON Data, Parsing JSON, Creating JSON, Working with XML, Using CSV Module, pickle Module for Serialization, YAML Format
  • Web Programming with Python: Requests Module, Web Scraping with BeautifulSoup, Using Scrapy for Advanced Scraping, Working with APIs
  • Numerical Computation with Numpy: Introduction to Numpy, Numpy Arrays, Array Indexing and Slicing, Array Operations, Broadcasting, Numpy Functions, Working with Matrices
  • Data Manipulation with Pandas: Introduction to Pandas, Series and DataFrame, Reading and Writing Data, Data Cleaning, Data Transformation, Merging and Joining, Data Aggregation

Introduction to RDBMS Database (SQL)

  • Introduction of RDBMS: Definition of RDBMS, Characteristics of RDBMS, Advantages of using RDBMS, Data Models in RDBMS, Keys in RDBMS (Primary Key, Foreign Key), RDBMS vs. NoSQL, Popular RDBMS Software
  • Installing and Using MySQL: System Requirements for MySQL, Downloading and Installing MySQL, Configuring MySQL Server, MySQL Workbench Overview, Connecting to MySQL Server, Basic MySQL Commands, MySQL User Management
  • Querying Single Table: SELECT Statement Basics, Filtering Data with WHERE Clause, Sorting Data with ORDER BY Clause, Using LIMIT to Restrict Rows, Aggregation Functions (COUNT, SUM, AVG), Grouping Data with GROUP BY, Handling NULL Values
  • Modifying Data and Table Structures: Inserting Data (INSERT INTO), Updating Data (UPDATE), Deleting Data (DELETE), Modifying Table Structure (ALTER TABLE), Dropping Tables and Databases, Adding and Removing Columns, Renaming Tables and Columns
  • Querying Multiple Tables: Introduction to Joins, Inner Join, Left Join, Right Join, Full Outer Join, Cross Join, Using Aliases for Table Names
  • Constraints of SQL: Primary Key Constraints, Foreign Key Constraints, Unique Constraints, Not Null Constraints, Check Constraints, Default Constraints, Enforcing Constraints in MySQL
  • Importing and Exporting Data: Importing Data from CSV Files, Exporting Data to CSV Files, Using MySQL Workbench for Import/Export, Using LOAD DATA INFILE, Using SELECT INTO OUTFILE, Data Formats for Import/Export, Handling Errors During Import/Export
  • Working With Expressions: Arithmetic Expressions, String Expressions, Date and Time Expressions, Logical Expressions, Conditional Expressions (CASE), Using Functions in Expressions, Combining Expressions
  • Database Normalization: Introduction to Normalization, First Normal Form (1NF), Second Normal Form (2NF), Third Normal Form (3NF), Boyce-Codd Normal Form (BCNF), Advantages of Normalization, Denormalization
  • Grouping and Summarizing Data: Using GROUP BY Clause, Using HAVING Clause, Aggregate Functions (SUM, AVG, MAX, MIN), Counting Rows with COUNT, Grouping Sets and Rollup, Pivoting Data, Summarizing Data with Subqueries
  • Triggers & Cursor: Introduction to Triggers, Creating Triggers in MySQL, BEFORE and AFTER Triggers, Row-Level and Statement-Level Triggers, Managing Trigger Execution Order, Debugging Triggers, Use Cases for Triggers. Introduction to Cursors, Declaring Cursors in MySQL, Opening and Closing Cursors, Fetching Data with Cursors, Cursor Looping, Handling Exceptions in Cursors, Use Cases for Cursors
  • Functions: Built-in Functions in MySQL, String Functions (CONCAT, LENGTH), Numeric Functions (ROUND, CEIL), Date and Time Functions (NOW, DATE_ADD), Aggregate Functions (SUM, AVG), Creating User-Defined Functions, Using Functions in Queries
  • Designing and Creating a Database: Database Design Principles, Entity-Relationship (ER) Modeling, Creating ER Diagrams, Defining Tables and Relationships, Choosing Data Types, Setting Up Primary and Foreign Keys, Implementing Business Rules with Constraints
  • Exploring and Processing on Data: Data Exploration Techniques, Descriptive Statistics in SQL, Data Cleaning and Transformation, Data Integration from Multiple Sources, Using Subqueries for Data Processing, Analyzing Data Patterns, Using SQL for Data Reporting
  • Advanced Querying Techniques: Subqueries and Nested Queries, Common Table Expressions (CTEs), Window Functions, Recursive Queries, Dynamic SQL, Query Optimization Techniques, Advanced Join Operations.
Mathematics & Statistics
  • Introduction to Statistics: Definition and Importance of Statistics, Types of Statistics: Descriptive and Inferential, Applications of Statistics in Data Science, Basic Terminology: Population vs. Sample, Statistical Methods and Techniques, Role of Statistics in Decision Making
  • Descriptive and Inferential Statistics: Overview of Descriptive Statistics, Data Summarization Techniques, Visualization Methods (Charts, Graphs), Measures of Central Tendency and Dispersion, Overview of Inferential Statistics, Concept of Statistical Inference, Estimation and Confidence Intervals, Hypothesis Testing Fundamentals
  • Process of Statistical Study: Defining the Research Question, Data Collection Methods, Data Cleaning and Preparation, Data Analysis Techniques, Interpretation of Results, Reporting and Communicating Findings.
  • Sampling Techniques: Probability Sampling Methods, Simple Random Sampling, Stratified Sampling, Cluster Sampling, Systematic Sampling, Non-Probability Sampling Methods, Convenience Sampling, Judgmental Sampling, Quota Sampling, Sampling Errors and Biases
  • Measure of Central Tendencies: Mean (Arithmetic, Geometric, Harmonic), Median, Mode, Weighted Mean, Applications and Interpretation of Central Tendencies, Comparison of Different Measures
  • Frequency Distribution: Types of Frequency Distributions, Ungrouped Frequency Distribution, Grouped Frequency Distribution, Constructing Frequency Tables, Histograms, Frequency Polygons, Cumulative Frequency Distribution, Relative Frequency
  • Measure of Dispersion: Range, Variance, Standard Deviation, Mean Absolute Deviation, Quartiles and Interquartile Range (IQR), Coefficient of Variation
  • Probability: Basic Concepts of Probability, Rules of Probability (Addition and Multiplication), Conditional Probability, Bayes’ Theorem, Independent and Dependent Events, Applications of Probability in Data Science
  • Probability Density Function: Definition and Properties, Continuous Random Variables, Common Continuous Distributions (Normal, Exponential), Calculation of Probabilities using PDF, Examples and Applications, Relationship with Cumulative Distribution Function (CDF)
  • Types of Data Distribution: Normal Distribution, Binomial Distribution, Poisson Distribution, Exponential Distribution, Uniform Distribution, Log-normal Distribution
  • Skewness: Definition and Interpretation, Positive Skewness, Negative Skewness, Measuring Skewness (Pearson’s, Bowley’s, Kelly’s), Impact of Skewness on Data Analysis, Real-life Examples, Definition and Interpretation, Types of Kurtosis (Leptokurtic, Mesokurtic, Platykurtic), Measuring Kurtosis, Impact of Kurtosis on Data Analysis, Real-life Examples, Relationship with Skewness
  • IQR (Interquartile Range): Definition and Calculation, Importance of IQR in Data Analysis, Detecting Outliers using IQR, Comparison with Range, Applications of IQR, Examples and Case Studies
  • Hypothesis Testing: Definition and Importance, Null and Alternative Hypotheses, Type I and Type II Errors, P-value and Significance Level, Steps in Hypothesis Testing, Examples and Applications
  • Chi-Square Test: Definition and Applications, Types of Chi-Square Tests (Goodness of Fit, Independence), Assumptions and Conditions, Calculation and Interpretation, Examples and Case Studies, Limitations of Chi-Square Test
  • ANOVA (One-Way and Two-Way): Definition and Applications, Assumptions of ANOVA, One-Way ANOVA (Concept and Calculation, Interpretation of Results, Examples and Case Studies), Two-Way ANOVA (Concept and Calculation, Interaction Effects, Examples and Case Studies)
  • Multicollinearity: Definition and Impact on Regression Analysis, Detecting Multicollinearity (VIF, Tolerance), Causes of Multicollinearity,Handling Multicollinearity (Ridge Regression, Lasso), Examples and Applications, Case Studies and Real-life Scenarios
Machine Learning (ML)
  • Prerequisites to ML – Overfitting, Regularization, Feature Selection: Introduction to Overfitting and Underfitting, Techniques to Handle Overfitting, Regularization Techniques, Feature Selection Techniques, Feature Engineering Techniques, Dimensionality Reduction Techniques, Data Preprocessing
  • Linear Regression: Introduction to Linear Regression, Ordinary Least Squares (OLS) Method, Model Evaluation Metrics, Assumptions of Linear Regression, Multiple Linear Regression, Regularization in Linear Regression, Polynomial Regression
  • Logistic Regression: Introduction to Logistic Regression, Binary Classification, Model Evaluation Metrics, Multinomial Logistic Regression, Regularization in Logistic Regression, Handling Imbalanced Data, Model Interpretation
  • Decision Tree: Introduction to Decision Trees, Tree Building Algorithms, Splitting Criteria, Pruning Techniques, Handling Continuous and Categorical Variables, Advantages and Disadvantages of Decision Trees, Visualizing Decision Trees
  • Random Forest:Introduction to Random Forest, Building a Random Forest Model, Hyperparameter Tuning, Feature Importance, Out-of-Bag (OOB) Error, Advantages and Disadvantages of Random Forest, Applications of Random Forest
  • AdaBoost: Introduction to AdaBoost, Working Principle, Algorithm Steps, Types of AdaBoost, Advantages and Disadvantages of AdaBoost, Hyperparameter Tuning, Applications of AdaBoost
  • Gradient Boosting: Introduction to Gradient Boosting, Working Principle, Algorithm Steps, Types of Gradient Boosting Algorithms, Advantages and Disadvantages of Gradient Boosting, Hyperparameter Tuning, Applications of Gradient Boosting
  • XG Boost: Introduction to XGBoost, Working Principle, Algorithm Steps, Hyperparameter Tuning, Evaluation Metrics, Advantages and Disadvantages of XGBoost, Applications of XGBoost
  • LDA (Linear Discriminant Analysis): Introduction, Working Principle, Algorithm Steps, LDA for Classification, Advantages and Disadvantages, Comparison with Other Techniques, Applications of LDA
  • PCA (Principal Component Analysis): Introduction to PCA, Working Principle, Algorithm Steps, Interpreting Principal Components, Advantages and Disadvantages of PCA, Comparison with Other Techniques, Applications of PCA
  • KMeans and KNN:Introduction to KMeans Clustering, Working Principle, Algorithm Steps, Evaluation Metrics for KMeans, Advantages and Disadvantages of KMeans, Introduction to KNN (K-Nearest Neighbors), Working Principle of KNN
  • SVM: Introduction to SVM, Working Principle, Algorithm Steps, Kernel Functions, Advantages and Disadvantages of SVM, Hyperparameter Tuning, Applications of SVM

Natural Language Processing & Deep Learning (NLP & DL)
  • Forward Propagation: Definition and Purpose, Mathematical Formulation, Input Layer to Hidden Layer Transitions, Hidden Layer to Output Layer Transitions, Activation Functions in Forward Propagation, Computational Graphs, Example of Forward Propagation in Neural Networks
  • Back Propagation: Definition and Importance, Chain Rule of Differentiation, Error Calculation, Weight Adjustment, Gradient Descent in Back Propagation, Back Propagation in Deep Networks, Example of Back Propagation
  • Epochs: Definition of Epochs, Role of Epochs in Training, Impact on Model Performance, Epochs vs. Iterations, Monitoring Training Progress, Determining Optimal Number of Epochs, Overfitting and Underfitting Concerns
  • Weights and Bias: Definition and Role of Weights, Initialization of Weights, Role of Bias in Neural Networks, Adjusting Weights and Biases, Impact on Model Accuracy, Regularization Techniques, Visualizing Weights and Biases
  • Activation Function: Definition and Purpose, Types of Activation Functions, Sigmoid Activation Function, ReLU (Rectified Linear Unit), Tanh (Hyperbolic Tangent), Softmax Activation Function, Choosing the Right Activation Function
  • Gradient Descent: Definition and Purpose, Types of Gradient Descent (Batch, Stochastic, Mini-Batch), Learning Rate and Its Impact, Convergence Criteria, Gradient Descent Algorithm Steps, Challenges and Solutions, Examples of Gradient Descent
  • Loss Functions: Definition and Purpose, Mean Squared Error (MSE), Cross-Entropy Loss, Hinge Loss, Regularization in Loss Functions, Impact on Model Training, Selecting Appropriate Loss Function
  • Optimizers: Definition and Role, Stochastic Gradient Descent (SGD), Adam Optimizer, RMSProp, Adagrad, Momentum-Based Optimization, Comparing Different Optimizers
  • Finding patterns in text: Text Data Collection, Tokenization, Stop Words Removal, N-grams Analysis, Frequency Distribution, Part-of-Speech Tagging, Named Entity Recognition
  • Text Analytics: Definition and Importance, Text Preprocessing Techniques, Sentiment Analysis, Topic Modeling, Text Classification, Text Summarization, Applications in Various Domains
  • Applications of Social Media Analytics: Sentiment Analysis on Social Media, Trend Analysis, Social Network Analysis, Customer Feedback and Insights, Brand Monitoring, Crisis Management, Influencer Identification
  • Fine tuning the models using Hyper parameters: Definition of Hyperparameters, Hyperparameter Tuning Techniques, Grid Search, Random Search, Bayesian Optimization, Hyperparameter Impact on Model Performance, Practical Examples
  • Deep Learning for NLP: Overview of Deep Learning in NLP, RNNs for Sequence Modeling, CNNs for Text Classification, Transformer Models, Transfer Learning in NLP, Pre-trained Language Models, Applications and Case Studies
  • Word Embeddings: Definition and Importance, Word2Vec, GloVe (Global Vectors for Word Representation), FastText, Contextualized Word Embeddings, Evaluation of Word Embeddings, Applications in NLP
  • Taming big text, Unstructured vs. Semi-structured Data: Differences Between Unstructured and Semi-structured Data, Challenges with Big Text Data, Storage Solutions for Big Text, Data Cleaning and Transformation, Tools for Handling Big Text Data, Practical Examples, Case Studies
  • Wordnet: Overview of WordNet, Synsets and Semantic Relations, WordNet for Synonym Identification, Applications in NLP, Integrating WordNet with Other Tools, Practical Examples, Case Studies
  • Text Preprocessing: Tokenization, Lowercasing, Stop Words Removal, Stemming and Lemmatization, Handling Punctuation and Special Characters, Removing Duplicates, Practical Examples
  • Lemmatization and Stemming: Definition and Differences, Stemming Algorithms (Porter, Snowball), Lemmatization with WordNet, Impact on Text Data, Choosing Between Lemmatization and Stemming, Practical Examples, Case Studies
  • Feature Extraction from text:Bag of Words (BoW), Term Frequency-Inverse Document Frequency (TF-IDF), Word Embeddings, N-grams, Named Entity Recognition, Part-of-Speech Tagging, Practical Examples
  • Vocabulary and Document: Building a Vocabulary, Document-Term Matrix, Term Frequency Calculation, Inverse Document Frequency Calculation, Handling Out-of-Vocabulary Words, Practical Examples, Case Studies


Classroom Sessions

Ethans Pune provides highly professional and advanced training tailored to industry needs, with a strong emphasis on practical and project-based learning. Our program features interactive sessions with individual attention, online doubt-clearing sessions, and access to recorded backup sessions. Additionally, students benefit from a dedicated forum for addressing doubts and questions.

LMS (Learning Management System)

We offer free supplementary courses to enhance your learning and grasp the cross-functional demands of the industry. You will also have access to recorded sessions from your ongoing classes, along with study materials including assignments, projects, and POCs to guide you through your current modules.

Quiz, Assignments & POC's

Each course includes quizzes, hands-on assignments, and interview preparation tailored to each topic and module. Trainers provide assignments based on students' skill levels and project requirements, with an estimated duration of about an hour per day. These assignments focus on real-world company projects to ensure practical experience. Additionally, complementary study material is provided with every course.

E&ICT, IIT Guwahati Certification

We are affiliated with E&ICT, IIT Guwahati, and offer certifications recognized by top companies. These certifications are awarded based on assessments by industry experts, enhancing the value of your curriculum vitae and giving you an edge in your profile. Boost the weight of your resume by obtaining a course completion certificate upon successful completion of the course and projects from E&ICT, IIT Guwahati.

Real-life Case Studies

Ethans offers a range of real-time projects with practical use cases, allowing students to gain hands-on experience. This approach helps students grasp business requirements, perform detailed analysis, and tackle challenges associated with real-time implementation. By working on these projects, students not only understand theoretical concepts but also apply them in real-world scenarios.

Job Assistance Program

Upon successfully completing a course with Ethans, you may become eligible for our job assistance program. This program includes help with crafting a standout resume and optimizing online profiles to attract job opportunities. Additionally, our extensive alumni network of over 5,000 members actively shares job openings. More than 3,000 freshers and professionals have secured positions in top companies across India.

Advanced Certification in Data Science & AI FAQs

What are the prerequisites for Advance Certification in Data Science & AI Training in Pune?

Ethans Tech + E&ICT, IIT Guwahati Advance Certification in Data Science & AI program doesn’t require any prerequisites to start off.

Our program contains all the basic concepts needed to grab the data science & AI technique which includes logical building, programming techniques, data warehousing concepts, SQL, statistics and linear algebra.

Who should go for Advance Certification in Data Science & AI in Pune?

Our experience shows that individuals from non-IT backgrounds can successfully learn and apply data science. Our classes include a diverse mix of participants, ranging from those with just one year of experience to professionals with up to 24 years of experience. This training is ideal for freshers starting their careers, as well as for professionals like CA, CS, BCom graduates, and share brokers who want to integrate data science into their daily activities. It’s the perfect kick-off for newcomers and a valuable enhancement for seasoned professionals.

What if I have queries after I complete this course?

You will have lifetime access to our technical discussion forum, where you can resolve most of your doubts and queries. For additional assistance, you can connect directly with your faculty or reach out to the nearest Ethans support desk at

Who are the training instructors?

Our faculty consists of highly experienced IT industry experts and corporate trainers from renowned MNCs, bringing exceptional knowledge to the classroom. Beyond their teaching roles, they also engage in consulting assignments with leading Indian and multinational companies, providing practical insights from real-world scenarios. The impact of our remarkable trainers is so profound that Ethanians often recall their classes vividly even years later.

Will Ethans be providing any study materials?

Yes, absolutely. Upon enrollment, you will receive hard copies of the study material. Additionally, during the program, your instructors will share soft copies of the materials through the cloud. This ensures that you have access to both physical and digital resources throughout your course.

What types of courses are available at Ethans?

Ethans is a market leader in Cloud, Automation, and Analytics, including technologies such as Python, Data Science (Machine Learning, Artificial Intelligence), AWS, Azure, GCP, DevOps, Hadoop, Selenium, and Robotics Process Automation. We help both working professionals and freshers enhance their skills across a range of in-demand technologies to meet market needs.

Does Ethans provide Job Assistance?

Yes, as one of the top institutes, Ethans boasts an extensive network in the industry. We have collaborations with numerous companies that have successfully helped over 3,000 freshers secure placements and enabled working professionals to transition to top roles across India. Upon completing the course, you will be eligible for placement assistance to support your career advancement.

Does Ethans provide weekend classes for professionals?

While many institutes offer software training courses, only Ethans provides professional training on a range of in-demand technologies with flexible scheduling options. We accommodate both weekdays and weekends to suit the needs of working professionals.

What are the profiles and experiences of trainers at Ethans?

We have a large team of highly skilled and renowned professionals with extensive expertise in their respective technologies. Our trainers are supportive and foster a friendly learning environment that promotes positive growth. With substantial industry and teaching experience, many of our trainers have over two decades of experience in their fields.

Do I need to pay the complete fee lump sum or I can have an installment facility too?

We offer flexible payment options, including lump sum and EMI installments. Through our partnership with Bajaj Finance, you can opt for EMI payments at no extra cost. Although paying in full is preferred, we also provide the option to split the payment into six installments with bajaj. The first installment of 25% is due at the time of registration, with subsequent installments starting from the following month.



The fee which I will pay is refundable or transferable?

Cancellation by Student:

  • Before Batch Commencement: Students may cancel their enrollment up to 7 days before the batch commencement date for a refund, minus a processing fee of 20% of the total course fee against the administrative charges.

  • After Batch Commencement: Refunds will not be provided once the batch has commenced. If a student decides to withdraw after the start of the course, no refund will be issued, though they may be eligible for a partial refund based on the medical circumstances and timing of the withdrawal.


Cancellation by Ethans Tech:

  • Program Cancellation: In the rare event that Ethans Tech cancels a program before it starts, students will receive a full refund of the course fee or may opt to transfer to another program of their choice, subject to availability.

  • Class Rescheduling: If individual classes are rescheduled, students will be notified in advance and no refund will be issued. Rescheduled classes will be conducted at a time mutually agreed upon.

Refund Process:

  • To request a refund, students must submit a written request to the Ethans Tech accounts team, detailing the reason for cancellation and any relevant information.

  • Refunds will be processed within 15 business days of receiving the cancellation request. The amount will be credited to the original payment method.


Special Circumstances:

  • Refund requests due to special circumstances (e.g., medical emergencies, unforeseen events) will be reviewed on a case-by-case basis. Supporting documentation may be required for consideration.


Batch Change Charges:

  • Students wishing to change their batch after enrollment will incur a batch change fee of ₹5,000. This fee covers administrative costs associated with the change. Certification Delay: Please note that changing batches may result in a delay in certification, as it will depend on the schedule of the new batch. Students should consider this potential delay when requesting a batch change.


This policy ensures clarity and fairness in managing cancellations and refunds, and aims to accommodate both student needs and institutional requirements

What are the facilities and infrastructure at Ethans?

Ethans has a presence at four locations in Pune: Wakad, Hinjewadi, Kharadi, and Baner. However, the advanced certification program in Data Science and AI is available exclusively at our Wakad location. We look forward to gradually expanding across India with your support. Ethans is equipped with state-of-the-art infrastructure that fosters a pleasant, academically rigorous, and stimulating environment for both students and faculty.

Does Ethans provide facility to repeat the batch?

Upon enrollment at Ethans Tech, you receive a flexi pass that allows for a one-year re-joining option at the same branch and with the same trainer for an administrative charge of ₹5,000. Additionally, we provide online recorded sessions as backups. If you wish to change branches or courses, it is possible with nominal charges, subject to the institute’s norms and regulations.

Does Ethans provide Institutional Certification after the course?

We are affiliated with E&ICT, IIT Guwahati, and offer certifications recognized by top companies. These certifications are awarded based on assessments by industry experts, enhancing the value of your curriculum vitae and giving you an edge in your profile. Boost the weight of your resume by obtaining a course completion certificate upon successful completion of the course and projects from E&ICT, IIT Guwahati. ​

Does Ethan's conduct this training at Corporates?

Yes, as a market leader, we frequently engage in corporate training, leveraging our extensive network of corporate trainers and collaborations with several top MNCs. This strong industry connection provides valuable references and ultimately enhances placement opportunities for our students.

What is the admission procedure at Ethans?

There are two ways to register with Ethans Tech: online and offline.

Online Registration: Visit the enrollment tab on our website – – which will redirect you to the enrollment form. Fill in your essential details and proceed by paying ₹5,000 as the registration fee (which includes your standard course fees).

Offline Registration: You can contact and visit any of our nearest Ethans branches to complete the registration process with the assistance of our team at the Ethans Desk.

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.

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Our Testimonials

Hi, it was a great and quality experience to upskill in Python with Ethans Tech. The program is well-designed, and the trainer was highly experienced, presenting concepts clearly with real-time scenarios. The admin team is very helpful and always available for any coding or software assistance. The comprehensive support and practical approach make Ethans Tech stand out. I highly recommend Ethans Tech for anyone looking to enhance their skills. They ensure that every student understands each topic clearly and are always ready to help.

    Renuka Gudela Palteru
    Renuka Gudela Palteru

    Sr. Team Manager at Gallagher

    The courses at Ethans Tech are premium and well-structured. The instructors are always available to clear queries and provide prompt support whenever issues arise. An added bonus is the access to software, study materials, and certification for each course you enroll in. I've taken multiple courses here, and each one has been excellent. The quality and consistency are impressive every time I enroll. I highly recommend Ethans Tech and appreciate their outstanding service. Love these guys—salute to their dedication!

      Upender Negi
      Upender Negi

      Network Design Specialist at BT, UK

      The training is marvelous, and we are about to start a POC that will help us implement real-time scenarios. Overall, the sessions are good and interactive. Thanks for organizing all the classes. I am immensely satisfied with the course content, which includes pre-recorded classes and eight months of post-class assistance from experts. I highly recommend Ethans Tech for its exceptional corporate learning and training in cutting-edge technologies, tools, and languages. It’s truly the best institute for professional growth.

        Priyanka Tomar
        Priyanka Tomar

        Consultant at Credit Suisse

        I am a final-year college student with a keen interest in Cloud Technology. In February 2020, I joined the Amazon courses training program at Ethans. This program provided me with 100% practical hands-on training, covering programming languages, Big Data Hadoop, AWS, Azure, and SQL Database. The comprehensive training prepared me well for internships and job opportunities. The instructors were knowledgeable, and the curriculum was highly relevant to industry needs. Ethans is truly one of the best institutes for acquiring essential skills

          Gayatri Soni
          Gayatri Soni

          Intern at Ethans Tech

          The classroom sessions were delightful and engaging. While I don't have a strong command of Linux and Python, which made me feel like I was lagging behind at times, the overall learning experience was superior. The instructors were knowledgeable and supportive, making complex topics easier to understand. The hands-on projects and practical examples were particularly beneficial. Despite my initial challenges, I gained valuable insights and skills. With more proficiency in those languages, the learning experience is wonderful.

            Md Ashraf Khan
            Md Ashraf Khan

            Technical Service Engineer Expert, Fujitsu

            It was a great learning experience at Ethans Tech. The teaching skills are pitched perfectly, and the trainers are well-experienced and motivational. They ensure that every student understands each topic clearly and are always ready to help. This dedication to student success is what sets them apart. Thanks a bunch, Ethans, for developing my interest in coding. I highly recommend Ethans Tech for anyone looking to enhance their skills. Overall, a fantastic learning experience! I am immensely satisfied with the course content

              Anhadpreet Singh
              Anhadpreet Singh

              Student at Guru Nanak Dev Engineering College, Ludhiana

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