Data Science And Artificial Intelligence Course by E&ICT Academy IIT Guwahati

E&ICT Academy

IIT Guwahati

Data Science And Artificial Intelligence

Online Instructor-led
2576 Ratings

Become an expert in the field of Data Science and Artificial Intelligence, with this advanced certification program by E&ICT Academy IIT Guwahati, and FingerTips. This course includes learning from world-class industry experts, mentorship from E&ICT Academy IIT Guwahati Faculties, hands-on projects, doubt-solving sessions, career assistance & more.

Your Dream Career Is Just One Step Away

Program Rating
Program Duration
9 Months
Post-Program Job Support
6 Months
No cost EMI

Gain Competitive-Edge In Emerging Technologies Through Data Science And AI Program

Average Salary Hike
Career Transitions
Hiring Partners

Key Highlights

Learn from E&ICT Academy IIT Guwahati Faculty & Industry Experts

3 Guaranteed Interviews

Preparation of technical and HR interview rounds

Industry-oriented learning paths

20+ Industry projects & case studies

400+ hours of extensive learning

Industry-oriented curriculum

24*7 LMS Support

Dedicated Program Manager

Skills Covered

Data Science

Data Analysis

Data Visualization

Machine learning

Deep learning

Artificial Intelligence


Data Wrangling


Data Science

Data Analysis

Data Visualization

Machine Learning

Deep Learning

Artificial Intelligence


Data Wrangling


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Program Details

The Data Science and Artificial Intelligence program in collaboration with E&ICT Academy IIT Guwahati aims to provide a world-class learning experience with all the skills required in the field right from basic to advanced levels. Gain a competitive edge with our hands-on training in Data Science and Artificial Intelligence field.

What are the learning objectives of this Data Science course?

We are in an era where decisions are taken based on the data. The amount of data is increasing but analyzing it requires experts who convert the data into actionable form. This Data Science and Artificial Intelligence program in collaboration with E&ICT Academy IIT Guwahati will help you to gain job-specific skills required to grow in the field.

The course curriculum covers concepts like Python, Machine Learning, Deep Learning, NLP, and much more. The training comes with capstone projects and real-world Datasets to prepare you for the job role of Data Scientist.

What Important skills will you learn with this Data Science and Artificial Intelligence course?

In this Data Science and Artificial Intelligence course, you’ll learn Data Science, Data Analysis, Data Visualization, Machine learning, Deep learning, Artificial Intelligence, Python, Statistics, NLPmodels, SQL, and Data Wrangling.

What projects are included in this Data Science and Artificial Intelligence course?

Get an opportunity to work on Real-World Datasets of various industries like healthcare, e-commerce, social media, entrepreneurship, supply chain, and more. Learn from basics like cleaning a large amount of data, organizing it, and much more.

Who should take this Data Science and Artificial Intelligence course?

Anyone with a graduate degree in any field can apply and enroll in Data Science and Artificial Intelligence course. However, it is recommended to have a technical background or gain some programming language knowledge.Freshers and working professionals with any educational background are eligible for the course.

What are the prerequisites for this Data Science and Artificial Intelligence course?

Freshers or professionals aspiring to become Data scientists are recommended to have the following skills:

• Basic Technical Knowledge
• Basic knowledge of Programming Language

However, learners without the above knowledge can enroll in the program.

What type of job will I be suited for after completing this Data Science with Artificial
Intelligence course?

Learners who complete the Data Science and Artificial Intelligence course will gain the skills and can land their dream job easily. Jobs positions that you can apply for after completion of the course are:

• Senior Data Scientist
• AI Expert
• Machine Learning Expert
• Big Data Specialist
• Senior Business Analyst
• Applied Scientist

What is the total duration of this Data Science and Artificial Intelligence course?

The Data Science and Artificial Intelligence course is a total of nine months inclusive of practical Hands-On Training.

What is the typical course syllabus for Data Science and Artificial Intelligence course?

Data Science and Artificial Intelligence are wide domains. This course covers all the important aspects like Statistics & Mathematics, Python Programming, Data Science Fundamentals, Machine Learning, Deep Learning, and much more.

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Tools Covered

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  • Statistics & Mathematics For Data Science

    This Data Science and Artificial Intelligence certification Program provides you with a complete overview of Statistics and Mathematics. Learning this is a very significant skill for many Data Science Roles, which you can develop with this course.

    Course Content

    Statistics Fundamentals

    • Statistics is a vital input in the field of data science. The lesson covers an introduction to statistics, descriptive V/S inferential statistics, variables and types of variables, and other important concepts.

    Advanced Statistics

    • After learning the basics of statistics, the lesson will now cover the advanced concepts of statistics. The learner will explore hypothesis testing, null and alternative hypotheses, type I error Vs type II error, P-value, T-test, about Anova, Chi-Square analysis, and other important concepts.


    • This lesson provides an introduction to Probability, why we need probability, concepts of simple probability, and the Bayes Theorem. The learner will also learn about independent & dependent events, distributions, skewness & kurtosis, and different techniques of sampling.

    Linear Algebra

    • During this lesson, the learner will master different concepts of linear algebra such as scalars, vectors, matrices, and tensors with some basic properties of tensor arithmetic. Along with other important concepts like reduction, non- reduction, dot products, vector products, and matrix multiplication.


    • This module will give you the core idea of calculus and how calculus is an integral part of data science. Also, understand the derivatives and differentiation of calculus with visualization utilities. Get to know the partial derivatives And gradients chain rule.

    Linear Regression & Outlier Detection

    • Get complete exposure to what is linear regression in data science. Learn what is linear regression, the types of regression, its advantages and disadvantages, and lastly certain examples of linear regression.

    Optimization And Its Techniques

    • Optimization is a tool to make the existing features make work more efficiently. The lesson will begin with an introduction to optimization and will proceed towards explaining the types of Optimization.

    Stochastic Search

    • Stochastic search is a search algorithm that is used to optimize an object function. The module will cover what is stochastic search, the stochastic optimization technique, an introduction to PSO, and the Genetic Algorithm in detail.
  • Python Programming

    Python is one of the highest used programming languages and also the easiest one. Here you will learn all its features and its application. This exciting topic of Data Science features interactive sessions, hands-on projects, and mentoring.

    Course Content

    Introduction To Programming & Python

    • Learn what is python programming language, why python is important, and which industries work with python. Get to know the application and features of python in different industries and components of python.


    • Get In-depth knowledge of different built-in datatypes such as immutable data types, numeric data types, and mutable data types. We will further learn about the list, tuples, set, and dictionary.


    • Operators are used to perform different operations on variables and values. In this lesson, you'll master arithmetic, comparison, logical, bitwise, identity, and membership operator.


    • This lesson will take you through understanding what is regex functions with different python regex such as Metacharacters, Special Sequences, and Sets.


    • Learn about several different statements in Python such as If statement, If- Else statement, and nested IF statement in this lesson. Also, gain some practical knowledge by building a program to check the greatest among three numbers.


    • In Computer programming, loops are used to execute blocks of code multiple times without writing that code repeatedly. In this lesson, you'll learn While, For, and Nested Loops.


    • Functions are the block of code that can only run when it is called. In this Chapter, you'll learn different types of functions, Functions Arguments, how to create a Function, calling different Functions, then return values from a Function, and at last some function arguments.


    • Get a new perspective on problem-solving by using Recursion. Also Learn how to calculate factorial, Detect Palindromes and how to sort by using Quicksort.

    OOPS Concepts

    • In this lesson, you'll learn about Object-Oriented Programming ( OOP) in Python and its Classes and Objects. Also, there will be concepts of Polymorphism, Encapsulation, Inheritance, and Data Abstraction.

    Data Structures

    • Introduce yourself to the core data structure of the python programming language by mastering different types of Data structures in python such as Built-In Data Structure and User-Defined Data Structure.

    Error Handling

    • Errors detected during execution are called exceptions, In this lesson get a detailed overview of Exceptions Versus Syntax Errors, Try and except statements, Assertions, and how to raise an exception.

    Scikit-Learn Library

    • Scikit- Learn is a free machine learning library for python that supports numerical and scientific libraries. In this lesson, you'll learn how to install, use and load Dataset in it.
  • Data Science Fundamentals & Applications

    One of the most important modules of this certificate program is learning the fundamentals of Data Science and its applications. Here you will gain in-depth insights into what is data and its importance along with use cases of data science in different industries.

    Course Content

    Numerical Parameters To Represent Data

    • The lesson will let you play with numbers and statistical concepts. It covers statistical concepts like Mean, Mode, Median, Range, Standard Deviation, Variance, Quartile, IQR Covariance, Correlation between Data, Histogram, etc.

    Data Science V/S Data Analytics V/S Business Intelligence

    • Unlike basics, this lesson will cover in-depth insight into Data science, a detailed overview of data analytics, and detailed insights into the concepts of business intelligence.

    Importance & Applications Of Data-Science In Today’s Data-Driven World

    • In the module of Data Science Fundamental, this lesson will give you an overview of why data science is a so booming field. The lesson covers the importance and benefits of Data science, its applications, and finally the growing future of Data science.

    Roles Of Data Scientists

    • In the module of Data Science Fundamental, this lesson will give you an overview of why data science is a so booming field. The lesson covers the importance and benefits of Data science, its applications, and finally the growing future of Data science.

    Introduction To Databases And Its Types

    • A Database is a collection of a large amount of organized data, stored for easy access of data. The lesson covers the overview of Databases, types of Databases, Database components, and finally advantages & disadvantages of Databases.

    Steps Of Data Science & Machine Learning

    • The lesson is the ultimate guide for all aspirants. It will guide the learners with the Data Science process, Machine Learning steps, and how to implement all the steps and processes practically to excel in the field.

    Use Cases Of Data Science In Different Industries

    • Data Science is a concept that is now widely used in majorly all possible industries. The lesson will cover the application of Data Science in Healthcare, Transport& Logistics, and Telecom. Also, the learners will learn how to solve a case study of Data Science.
  • Introduction To ML & Dimensionality Reduction

    This introduction to Machine Learning is designed to help you unlock the mystery of machine learning and its application and uses. It also provides an overview of Dimensionality Reduction. At this stage, you will master the skills of Machine Learning.

    Course Content

    Introduction To Machine Learning

    • Get introduced to the machine learning program and reinforcement learning. Details on the types and used cases of machine learning. This sub-module is designed to understand the machine learning modeling flow and explore the supervised & unsupervised learning with the challenges of ML.

    Feature Selection

    • Ensure complete knowledge of what is feature selection. Get to know the reasons why it is such an important part of ML. Procedures to choose a feature selection model. Understand various models and feature selection with python.

    Feature Scaling

    • Learn the importance of feature scaling. The lesson gives you a good idea of the absolute maximum scaling in ML with the data ranging from min-max scaling to normalization, standardization, and robust scaling of data. Find out the reason if feature scaling is helpful.

    Principal Component Analysis (PCA)

    • Learners will explore the disciplines of business analytics and discover the Hypothesis Testing Part 1 and 2. The details of the Principal Component Analysis and Principal Component Analysis Case Study will clear the concepts of PCA.

    Discriminant Functions

    • All the details on Linear Discriminant Analysis (LDA), will be covered in this sub-module. This lesson also highlights important aspects of the statistical methods of quadratic discriminant analysis with extensions to linear discriminant analysis and common LDA applications.

    Linear Discriminant Analysis (LDA)

    • It will be an informative experience to understand all about Linear Discriminant Analysis (LDA) with its assumptions. The sub-module will elaborate more on intuitions and mathematical descriptions of LDA. Learning the model parameters will add more value to your skills.

    Exploratory Factor Analysis (EFA)

    • It will be an interesting session to discover what is EFA. This lesson will cover what To Include In An Exploratory Factor Analysis and the methods of EFA Vs. CFA, with the assumptions of EFA.
  • Python For Data Science

    The module provides an understanding of the application of python in data science and its importance in the current world. The focus will be on developing insight in Analytics, data visualization, and data manipulation with Python.

    Course Content

    NumPy For Mathematical Computing

    • NumPy is one of the libraries of python that is used to work with arrays. Learn Arrays and Matrices, Array Indexing, Array Math, Inspecting A NumPy Array, NumPy With Conditional Expressions, and other important concepts.

    Data Manipulation With Pandas

    • Panda is a combination of two different libraries i.e. Matplotlib and NumPy. Learn various concepts in this module such as DataFrame in Pandas, Series object in pandas, Loading and handling data with Pandas, merging with joins, and much more.

    Data Visualization With Matplotlib And Seaborn

    • Data visualization is the process of representing the data in the form of charts, graphs, and other visual designs to understand the data better. Learn what is Data Visualization, and Matplotlib, and use Matplotlib for Plotting Graphs.

    Exploratory Data Analysis

    • Data Analysis is a process of firstly examining and understanding the data and then extracting useful insights from that data. In this lesson, you will learn market analysis with exploratory data analysis, exploratory data analysis techniques, and much more.
  • Supervised Learning And Discriminative Models

    Supervised learning, also known as Supervised Machine Learning is part of Machine Learning and Artificial Intelligence. The concept is used to classify the data and predict the solutions. The course will help you understand Perceptron, K-NN and RBF, ANN, Decision Trees, Random Forest, and much more.

    Course Content

    Introduction To Supervised Learning

    • The first lesson in the module includes a basic understanding of concepts, types of supervised learning, real-life applications, and the flow of supervised learning algorithms.

    Linear Regression

    • Linear Regression is using a straight line to find a relation between the independent and dependent variables. The lesson will cover Multiple Linear Regression, Lasso Regression, Ridge Regression, and other topics.

    Logistics Regression

    • Logistic Regression is used to estimate the relationship between a dependent variable and one or more than one independent variables. This lesson will cover Sigmoid Function and Decision Boundary, different assumptions of logistic regression, advantages, and disadvantages, and other topics.

    Classification And Regression Trees

    • This module will cover Decision trees, classification, and differences in regression trees, Their advantages, and limitations. It will also have in-depth knowledge of how Classification and Regression trees work.

    Decision Trees and Random Forest

    • Get yourself ready to Set-up the environment of Decision Trees and Random Forest in this lesson. This module will cover all of the concepts like Decision Tree Metrices and Random Forest as Ensemble learning.

    Support Vector Machine (SVM)

    • At the start of this lesson learn about support vector machines, their advantages, and disadvantages with some popular applications of SVMs, and Kernel functions. Also, Get a demonstration of Support Vector Machine in python.

    K- Nearest Neighbor And Support Vector Machine

    • This lesson will start with a complete In-depth understanding of K-Nearest Neighbor with complete insights into the Support vector machine.

    Bootstrapping And Boosting

    • Ensemble machine learning can be mainly categorized into bagging and boosting. In this lesson, Work with Prediction Errors, different Ensemble Methods, and the main differences between Bagging and Boosting.
  • Unsupervised Learning, Generative Models, And Pattern Discovery

    Supervised learning, also known as Supervised Machine Learning is part of Machine Learning and Artificial Intelligence. The concept is used to classify the data and predict the solutions. The course will help you understand Perceptron, K-NN and RBF, ANN, Decision Trees, Random Forest, and much more.

    Course Content

    Introduction To Unsupervised Learning

    • Unsupervised learning is the machine learning technique algorithms that analyze untagged data. This sub-module will help you understand the common approaches to unsupervised learning. You will understand the different applications and challenges of unsupervised learning.

    Spherical K-Means And Incremental Clustering

    • Spherical K-Means is an unsupervised algorithm that maintains the length of the vector parameters which may differ the direction but not the magnitude. Understand the types of clustering. Get introduced to spherical k-means clustering & Incremental Clustering.

    K-Means Clustering

    • K-means clustering is a refined method that clusters the analysis in data mining & statistics. This lesson will help you find out applications of k-means clustering with distance measure tasks. Get engaged with the details and demo on the k-means clustering.

    Hierarchical Agglomerative Clustering And DBSCAN

    • Hierarchical Agglomerative Clustering is a free machine learning algorithm used to group untagged datasets into a cluster. It is the most important method in the clustering process. This chapter will give you more exposure to the process of agglomerative hierarchical clustering and Density-Based Spatial Clustering (DBSCAN).

    Mean-Shift Clustering

    • Mean-sift clustering is an ace data clustering algorithm used in image processing and computer vision. Get to know the important aspects of kernel density estimation, mean shift, and implementations in Python.

    PLSA & Sequence Mining

    • Probabilistic Latent Semantic Analysis (PLSA) is a statistical technique for the analysis of semantic data. You will learn the concepts and applications of sequence pattern mining with different types of sequence learning pattern mining patterns.

    Association Mining Rule

    • The Association mining rule is a process of observing similar patterns or connections from datasets found in different datasets like a transactional or relational database. It will be an informational experience to attend the session on understanding the types and algorithms of association mining rules in data mining.

    Hidden Markov Model (HMM)

    • Hidden Markov Model (HMM) is used in machine learning to depict the progression of recurring events that depend on in-house factors, which are not directly visible. This class will provide the study of HMM with examples. Know details on the application of HMM and HMM in Natural language processing (NLP). Extract details on part of speech tagging (PoS) with HMM and implementation of python.
  • Machine Learning & Cloud

    With this Data Science and Artificial Intelligence program, learn the concepts of Machine Learning and Cloud. Learning these concepts is important to understand the core of Data Science and Machine Learning. The curriculum will help you gain all the skills required in the field.

    Course Content

    Cloud Fundamentals

    • In this lesson, you'll learn about the basics of cloud computing, its features, Cloud services with pricing, and how you can easily build a business case for the cloud.

    ML Tools On Cloud ( AWS, Azure, GCP)

    • Start with the main concepts of Machine learning, different types of machine learning tools, and some cloud-based services like Amazon Web Service, Microsoft Azure, and Google Cloud Platform.

    Deploying ML Project on Cloud

    • In this lesson learn how to store different ML models in cloud storage then set them up in the cloud storage bucket and at last get trained on how to upload exported models to cloud storage.
  • Deep Learning

    Learn the important elements of Data Science i.e. Deep Learning in this module. Master concepts of Deep Learning in this module like CNN, RNN, DNN, etc.

    Course Content

    Introduction To Deep Neural Network

    • Start with the basic concepts of deep learning, the History of Deep learning, Challenges, Applications, and the difference between Machine Learning and Deep Learning. Also, you'll learn about the general flow of deep learning projects.

    Introduction With TensorFlow

    • Get yourself introduced to Tensorflow, the Hello World Program of TensorFlow, and Deep Neural Networks. This Module will also cover Linear and Logistic Regression With TensorFlow.

    Convolutional Neural Network

    • In this lesson on Deep Learning, you will understand how Computer Vision and Convolutional Neural Network has evolved, covering CNN design and Architecture, Convolutional layer, Padding, Stride, and different layers. Also, you'll work on Feature detectors and Feature maps.

    Implementation Of ConvNet/CNN From Scratch

    • This lesson will start with an Introduction to CNN and how CNN recognizes different images. Also, there will be a detailed introduction about the layers in a Convolutional Neural Network with some use case implementation using CNN.

    Recurrent Neural Network

    • Learn about one of the best Deep Learning architectures yet! This lesson will teach you about the architecture of RNN, backpropagations in RNN, and Some of its applications and problems. You'll also learn when to use Long short-term memory ( LSTM).

    Deep Learning Applications

    • Deep Learning has revolutionized everything by making tasks easier in almost every sector of business. In this particular lesson, you will get knowledge on Image Processing, Natural Language Processing, Chatbots, Computer Vision, and Object detection with Audio Analysis.
  • Speech, Vision, NLP

    The module deals with NLP where you learn Image Processing, Language Models, and NLP Libraries. Unlock your Career by learning In-Demand Skills from FingerTips Data Science and Artificial Intelligence program.

    Course Content

    Image Processing Using OpenCV

    • Open source computer vision library is an open source that includes numerous computer vision algorithms. You can probably do all the computer vision tasks in a wide range. Learn the technics of the tool that perform multiple image processing functions.

    Signal Processing

    • Signal processing is a technique that shapes content in signals to provide the ASR (Automated speech recognition). It helps to filter the data from speech signals and translate it into words. Get the opportunity to get details on signal processing on GPUs and FPGAs and how signal processing will forefront data analysis.


    • In this lesson you will end up experiencing Scipy, it is all about the fundamental algorithms for scientific computing in Python. All important aspects related to Scipy will be covered in this sub-module.

    Introduction To Natural Language Processing (NLP)

    • Natural language processing (NLP) is an important branch of AI. It is related to the interaction system between the computer and human language. This class will throw light on text mining and NLP details.

    Language Models

    • This will be an interesting lesson targeting language models. A language model is a machine learning model designed to equate the language domain. Language model Importance and various uses of LM. You will be getting a good idea of how language models work.

    Vector Semantics

    • Vector semantics is a model that explains various prospects of words such as word similarity, word senses, grammatical explanations, etc. It will be an engaging session to know why the vector model is important and what is TF-IDF.

    NLP Libraries

    • Natural language processing (NLP) is a field that emphasizes making natural human language usable by computer programs. Understand various open-source libraries for Natural Language Processing in Python. The sub-module will focus on various NLP libraries.
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Self-Paced Learning

Get access to high quality self-paced content curated by top industry experts. Here you will be exposed to the variety of concepts of Data Science and Artificial Intelligence, that you can learn at your own pace - anytime, anywhere.

  • MySQL

    MySQL is a relational database management system based on the Structured Query Language. It is the popular language that helps you in accessing and manage the records in the database. This module includes all topics of MySQL starting from how to manage databases to manipulate data with the help of various SQL queries to writing subqueries.

    Course Content

    Introduction to Database

    • This sub-module will explain all about the database and its components.

    Introduction to SQL

    • Have a hands-on learning experience in structured query language and different types of databases. Get to know the RDBMS and implement data modeling and different queries.

    SQL Operators With Syntax

    • This session will help you understand all types of SQL operators. Gain experience with arithmetic operators and implement comparison, logical, compound, and unary operators to filter data.

    Working With SQL: Join, Tables, and Variables

    • Experience a productive session about SQL with detailed databases, variables, and tables technique and functionality.

    Writing Subqueries in SQL

    • Get an informative session on subqueries in SQL and applications. You will be learning various techniques and methods to create subqueries. Get an up hand experience in implementing different subqueries with industry data.

    SQL Views, Functions, And Stored Procedures

    • This sub-module will guide you on various aspects of SQL views, functions, and stored procedures. At the end of the session, you will implement and understand the benefits of SQL Views.

    Advance SQL

    • Experience an elaborate class on advanced SQL. Get well-defined information on SQL functions constraints attached to it. Explore more about sub queries. Implement Various Joining, Union, Grouping, and Filtering operations and get a practical hand on working with industrial data.
  • Data Analytics with Excel

    In this course, you will learn why data analytics is crucial in today's industry to make an informed business choice and how Excel can assist you in doing so. This course walks you through the specifics of data analytics and uses a variety of examples to help you comprehend the many areas in which data analytics is essential.

    Course Content

    Overview Of Advanced MS Excel 2019

    • The module covers detailed excel features with its applications and knows all about the industry requirements of Excel.

    Custom Data Formatting In Excel

    • Grasp complete technical understanding about formatting, every prospect from formatting techniques to various functions.

    Basic & Advanced Data Sorting

    • The module will explain all about basic & advanced data sorting in excel. Get to know all details on various sorting orders, like sorting by number, and text, sort data by cell color, font color, and so on.

    Conditional Formatting

    • This module will make you aware of the various uses of highlight cell rules. At the end of the session, you will know all about conditional formatting.

    Advanced Formulas & Functions

    • You will be learning advanced formulas & functions in excel.
      By the end of the session, the user will be able to solve all complex calculations.

    Advanced Data Validation

    • Data validation is the method to keep your users informed about values in a cell and guide them to select something particular.The session will cover formula-based alidation, dropdown list input message, error message, etc.

    Lookup And Reference Functions

    • The Lookup function allows you to find a piece of data in a row or column. Get complete knowledge on the use of LOOKUP along with lookup and Hlookup functions.

    Index Match

    • This session will give you a good idea of how the index function returns a value from within a table. Know all about the match functions. Get to know the difference between index match and vlookup.

    Data Security In Excel

    • With the option of password protection, you can prevent your worksheet from being visible to other users. You can prevent your worksheet from adding, deleting, and renaming by other users. This lesson will guide you on all data security measures in excel.

    Data Analysis With Pivot Tables

    • Data analysis is a meaningful aspect of excel. A vast amount of data values are abbreviated to achieve the required results. This module will help you understand what role is played by pivot tables for data analysis. Explore all about pivot table analysis and design options.

    Sorting, Filtering, And Grouping Data With Pivot Tables

    • You will be learning the important features of pivot tables in excel. All about sorting, filtering, and grouping data with the pivot table. The session will provide you with interesting information on pivot table report filter pages.

    Enriching Data Table Calculated Values & Fields

    • The learners will pick up effective information on advancements in data table values and fields and define calculated fields with pivot tables.

    Excel Pivot Table Case Study

    • The excel pivot table case study in the module will highlight setting the expectations and analyzing U.S. voter demographics.

    Data Visualization With Excel

    • Excel charts and graphics are the visual representation of data, it makes it easier for users to analyze the data values. Learn various functions and types of charts in this session.

    Visually Effective Excel Dashboards

    • A dashboard is an optical display of the data. The module will cover the best practices of excel dashboard design and various dashboard utilities and functions.

    Excel MACROS

    • Macros is a function that automates the task which you have to do it repeatedly. This module will enlighten more information on macros with all their functions and practical use of macros in excel.

    Excel VBA

    • Visual Basic Analysis is a Microsoft programming language for MS Excel, MS-word, and MS Access. The session will highlight the excel VBA editor, VBA concepts, VBA procedures, and its functions.

    Data Table

    • The data table is the most basic structure of business intelligence. It is a simple form with rows and columns which represent the data values. Get to know how to set up the data table and create a data table with a single input.

    How To Create A Date Table To Get Multiple Results

    • After learning to set up and create the data table with a single input, learn how to create a data table with multiple results. Learn more about two inputs in the data table.

    Scenario Manager

    • A scenario is a set of values that Excel saves and can generate an automatic alternative of data on your spreadsheet. The sub-module will focus on different types of scenarios. You will be learning how to create a scenario, use scenario manager and independently create summary reports with various scenarios.
  • NoSQL- MongoDB

    MongoDB is an open-source document database and leading NoSQL database. Below are some of the key concepts and terms that you will learn in this module.

    Course Content

    Welcome To World of NoSQL and MongoDB

    • Learn different types of Databases along with Challenges, Benefits, and types of RDBMS. This lesson will also give you an in-depth introduction to MongoDB with its complete installation process.

    CRUD And Basic Operations

    • CRUD operations will develop a comprehensive understanding and help in creating, reading, updating, and deleting documents. In this lesson, you will learn how to create databases & collections, JSON data, and BSON data. Also, you'll learn about finding, deleting, updating elements, and projection.

    Schema, Modeling, And Relations

    • This session is all about understanding schema, Data models, types of data models, and more. Some more concepts of tree structures, Relationships will also be covered.

    Indexing And Aggregation Framework

    • Indexes help in the quick execution of queries in MongoDB. Aggregation in MongoDB, process data records, and return computed results. In this lesson on Indexing and Aggregation Framework in MongoDB, you will understand Indexing and Aggregation concepts, their types, properties, and also about performance tuning.

    Replication & Sharding

    • Learn concepts of Replication and Sharding, their working in MongoDB, Replication setup, and more. This session will also cover other concepts of Query Router.

    Data management and Administration

    • Monitor different issues and levels in Databases and Servers, Database profiling, Memory usage, Page fault, and Different methods to Backup, Recover, Import, and Export from MongoDB.

    MongoDB Security

    • This session will be all about creating, updating, and assigning users in MongoDB. It will also cover the part of the integration with java in MongoDB.

Industry Projects

In this certificate program, you would also get real-life exposure through Industry Projects along with the mentorship from E&ICT Academy IIT Guwahati Faculty. These projects will be a part of your Certification in Data Science & Artificial Intelligence to enhance your knowledge. You will be working on real-world datasets under the guidance of world-class industry experts.

Certification from E&ICT Academy IIT Guwahati

This unique Data Science with AI Certification program is brought to you in collaboration with E&ICT Academy IIT Guwahati. The initiative of the Ministry of Electronics and Information Technology (MeitY), E&ICT Academy IIT Guwahati is formed with highly knowledgeable professors to offer quality education programs. With a curriculum co-created by E&ICT Academy IIT Guwahati professors, live classes from IIT Faculty and Industry Experts, gain the essential skills to master the field of Data Science and Artificial Intelligence.

  • Upon successfully completion of this course, you will:

    Receive an Advanced Certification in Data Science and AI from E&ICT Academy IIT Guwahati.

Career Assistance

Why Fingertips?

  • 2x Faster Career Growth

    We have a participative and activity-based learning mechanism to help you master the most in-demand skills that most of the top companies are looking for.

  • Real-World Projects

    You get hands-on exposure to industry-relevant live projects related to Data Science and Artificial Intelligence.

  • Doubt-Solving Sessions

    There is distinctive support for Non-Technical learners with regular doubt-solving sessions by industry experts.

  • Dedicated Program Manager

    A separate instructor i.e. a Dedicated Program manager will be with you to guide you during the entire certificate program.

  • 24/7 LMS Support

    Get access to a customized in-house portal, 24/7 accessibility, with integrated teaching assistance.

  • Career Support

    Thorough facilitation for personal mentorship, profile building, interview preparation,and follow-up after successful completion of the course.

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Success Tales

Binz Joshep
B.E (Computer Engineering) Data Scientist

From a fresher to an expert, it was the right decision to invest in this course. Fingertips upskilled me with expert learning and that too with a reasonable data science course fee.

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Anil Rajput Data Scientist

I’m delighted to share that I enrolled with Fingertips for Data Science Program. The mentors are experienced in the field and provide industry-oriented learning. The course design is fit for learners from even non-technical backgrounds.

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Prerana Niwadunge Data Analyst

The all-inclusive, learning journey with Fingertips was amazing. With expert trainers, Hands-on assignments, and case studies, I got an edge in the industry and had an advantage over others.

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Parin Masuri
Mechanical Engineer Data Scientist

I had an amazing experience in learning Data Science from Fingertips. The support from the technical and career Assistance team was wonderful. According to me, Fingertips is the best option to learn this course from.

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Bhumik Vyas
B.Sc Physics (Fresher) Data Scientist

I pursued a data science online course from Fingertips and it was a Hands-down the best experience. A special thanks to all the faculties at Fingertips for making my learning journey smooth.

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Dhurti Vyasa
B.Sc Physics (Fresher) Data Scientist

Fingertips provide the best Data Science certifications that are valuable in the Industry. I gained theoretical as well as practical knowledge from the course and got Industry-ready with the faculty's guidance.

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Khanjan Dhariya
Non-Tech Data Scientist

I got In-demand with Fingertips. A course designed according to the need of Industry, Fingertips have created Hands-down the most Ideal course in the Data Science Field. Also, the support team of Fingertips is ready to help the learners whenever needed.

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Our Alumni Work At

Course Fees

*No cost EMI Option Available

Total Admission Fee

• 9 Months Program

• Certification from E&ICT Academy IIT Guwahati

• Online from Fingertips

• 100% Job Asistance

(excl. taxes)

Financing Partners

We have partnered with the following financing companies to provide no-cost EMI and competitive finance options with no hidden costs.

Frequently Asked Questions

Why should I enroll in Data Science and Artificial Intelligence program?

According to Harvard Business Review, Data Science is the most in-demand job of the 21st century. The demand for professionals in the field is only going to grow. Along with Data Science, other fields like Machine Learning, Artificial Intelligence are rising. The course with dual proficiency will help the learners to land a notable role in the field.

Who should enroll in this program?

With the high demand for Data Science and Artificial Intelligence in a wide range of industries like banking and finance, manufacturing, transport and logistics, healthcare, home maintenance, and customer service, it is a solid career choice for both fresher and experienced professionals. This Data Science and Artificial Intelligence program is well suited for a variety of profiles like:
• Beginners or recent graduates looking to build a career in Artificial Intelligence and Data Science
• IT Professionals aspiring to be a Data Scientist or Artificial Intelligence Engineer
• Business Analysts and Software developers who are aiming to level up their careers.
• Developers and Project managers who want to gain expertise in Data Science and AI algorithms.

What roles can a Data Science and Artificial Intelligence Professional play?

This program helps you prepare for Data Scientist and Artificial intelligence roles like Senior Data Scientist, AI Expert, machine learning Expert, Big Data Specialist, Senior Business Analyst, and Data Analyst roles.

Who will be my mentors?

In this program, you will learn from IIT Faculty and the top-notch data science and artificial intelligence industry experts. You will also have 1:1 interactive and doubt-solving sessions with experts. This certification program is designed to make you industry ready, wherein you will also get hands-on training with self-paced learning co-developed by the faculty of E&ICT Academy IIT Guwahati.

What if I miss attending one or more lectures?

If, in any circumstances, you miss attending the lectures, we will send you a copy of the recorded session in the next 24 hours. However, in case of any queries, you can also connect with the dedicated program manager.

I am a fresher; can I participate in the Data Science and Artificial Intelligence program?

This Data Science and Artificial Intelligence program is well suited for various profiles. A recent graduate can also apply for this course. We have a participative and activity-based learning mechanism, where you learn even complex subjects easily and creatively from our trainers. We also offer other supporting courses to help you learn Data Science and Artificial Intelligence from scratch.

How do I become a Data Scientist?

One can become a certified Data Scientist professional with FingerTips Data Science and Artificial Intelligence Program. The program covers all the important aspects to get you going in the field. The learners will also earn a certificate after completion of the curriculum.

What will be the duration of the campus Immersion?

Learners can visit the campus at E&ICT Academy IIT Guwahati, for a 2-day campus immersion session where they can learn from IIT Faculty and interact with their classmates. However, this is dependent on the pandemic and guidelines by the institute. This facility will be optional for the students; however, the cost of the two-day program will be borne by the learner.

How will the certificate be awarded?

After completing the program and all the requirements, the learner will be awarded a certificate from E&ICT Academy IIT Guwahati.

What services are included under career assistance?

The learner will get 360° career assistance in profile building and interview preparation sessions from our industry experts. Also, it includes mock technical interviews conducted by experts’ panels followed by feedback for improvement.

Why should I choose FingerTips for Data Science and Artificial Intelligence Program?

Fingertips is one of the leading ed-tech companies. We offer comprehensive and industry-relevant tech courses across various domains, including Data Science, Artificial intelligence, Big Data, Business Intelligence, and other domains. Since its inception, we have trained more than 20000 learners in various fields and successfully placed 95% of trainees in big corporates. Our highly rated live and online instructor-led training is designed according to the suitability of learners. The use of cutting-edge technology, customized curriculum, and continuous innovations in the learning process makes us special in the industry.

How is data science related to artificial intelligence?

Basically, data science is making raw data intelligent with the concepts of machine learning and deep learning. Moreover, Data Science uses the algorithms of machine learning, resulting in the dependency on artificial intelligence. In short, machine learning is the connecting link between data science and AI, as it is the branch of AI used to build insights from data.

What is the refund policy for this program?

As per the policy, 20% of the course fee is kept aside as a non-refundable amount. The remaining 80% will be finalized on a pro-rata basis i.e based on the 3 months or 6 months option selected by you. Kindly refer to our Refund Policy for more details.

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