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Artificial Intelligence Specialization Program

This Artificial Intelligence online program is created to help students learn Python Programming and its application to Data Science, Machine Learning, Deep Learning and Text Analytics. This is followed by hands-on experience in solving problems using Deep Learning to get a real-time experience of Data Science projects.


  • Essentials of Python Programming and Introduction to Libraries
  • Data Exploration with Statistics
  • Data Visualization
  • Machine Learning Techniques
  • Deep Learning
  • Text Analytics
  • Projects


200 hours


Weekends – 6 hours
9.30 PM IST to 12.00 PM IST



Online Live

Instructor-led online live in-depth sessions


Get a course completion certificate


2 way communication via text & speech


Free Trial Class

Get a Demo class before Registeration for assured learning

Industry Projects

Multiple domains specific projects & discussions


Small Batch Size

15-20 students per batch for 1-to-1 interactions

Cloud Based Lab

Cloud-based online lab for hands-on training


Job Assistance

Assistance in resume building & placement


Statistics Fundamentals

Descriptive and Inferential statistics concepts and implementation using real-world data will also be covered. It will end with a case study implementation of EDA.


  • Descriptive Statistics
  • Inferential Statistics

Python Programming

Python is a critical tool for Data Science. In this module participants learn Python programming from basic to advanced level using Jupyter notebooks. Here, participants create, subset and manipulate various data structures. Specific libraries like NumPy, Pandas and Matplotlib that are popular for Data Analysis are covered in depth.

    -Numpy Library
    -Pandas Library
    -Matplotlib and Seaborn Library

Machine Learning using SciKit Learn (Python)

Machine Learning algorithms are the backbone of Predictive Modelling. This is where the Crux of Data Science lies. The end objective of solving a data science problem is finding the patterns in the data and represent that in the form of a Data model. The algorithms taught in our course cover almost all of the problems data scientists solve on a regular basis.

  • The Machine Learning Landscape
  • Supervised Machine Learning
  • UnSupervised Machine Learning

Deep Learning

In this module, participants will learn the foundations of Deep Learning and understand how to build neural networks. The implementation of the same will be done using Python, TensorFlow and Keras.

  • Deep Learning Fundamentals
  • Working with Keras
  • Training Deep Neural Networks
  • Deep Computer Vision Using
  • Convolutional Neural Networks
  • Pretrained Models for Transfer
  • Learning
  • Classification and Localization
  • Object Detection

Text Analytics

Natural Language Basics

  • Introduction to Natural Language processing
  • Processing and Understanding Text
  • Text Classification
  • Text Similarity and Clustering
  • Semantic and Sentiment Analysis

Data Visualization using Tableau

Tableau is one of the most popular Data Visualization tools used by Data Science and Business Intelligence professionals. In fact, it has been the market leader in reporting tools for almost 10 years (Source: Gartner magic quadrant). Once the predictive analysis of data is done, data scientists generally use Tableau to send out the reports to business which can then take decisions accordingly.

  • Intro To Data Visualization and Tableau
  • Data Connections – Joins and Vizql
  • Building Basic Charts, Chart Types And Mapping
  • Aggregation, Parameter
  • Statistical Analysis Using Tableau – Regression and Box Plots
  • Table Calculation, Calculated Fields
  • Dashboarding
  • Integration Of Python with Tableau

R Programming [Recorded]

R is one of the most commom languages used in Data Science.

  • Fundamentals of R Programming – Working with RStudio
  • Data structures & data types in R
  • Functions
  • Control Structures
  • Data handling in R – Importing and Exporting Data
  • Cleaning and Manipulating Data

Case Studies

  • Work on multiple Case Studies of Machine Learning and Deep Learning.


    Choose from a set of projects and work on at least a couple of projects under the guidance of the mentors to create a portfolio for business. Projects include problems that would be solved using Traditional Machine Learning models and Deep Learning algorithms.



    • Online Classes [Get the services of best trainers from Anywhere]
    • LIVE instructor-led training throughout the training duration
    • Entirely Hands-On driven session
    • Practical Inputs from real-time scenarios
    • Problems and Case Study driven training
    • Machine Learning algorithms are taught using at least 2 Case Studies for every algorithm


    Kushagra, (IIT Delhi – 10+ years experience in Analytics & data science), has a keen interest in Problem Solving, Deriving insights & Improving the efficiency of processes with new age technologies.

    He’s good with statistical concepts and possess thorough business understanding along with practical experience in linear models (like Linear Regression, Logistic Regression, Ridge Regression, Lasso Regression),

    Tree based algorithms (like Decision trees, Bagging, Random Forest, GBM, XGBoost), clustering (like K-Means, Hierarchical),Time-series analysis (like ARMA, ARIMA, stationarity), Deep learning(CN, RNN), NLP Techniques(TFIDF, LDA, Topic Modelling) Extensive knowledge of Tools like R,Python, Spark, Tensorflow, Keras, Tableau. Trained 5000+ participants in R, Machine Learning, Tableau and Python, Big Data Analytics at Dimensionless Conducted workshops and training on Data Analytics for Corporate and Colleges

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    HIMANSHU (IIT, Bombay – 10+ years experience in Data Science) A machine-learning practitioner, fascinated by the numerous application of Artificial Intelligence in the day to day life.

    I enjoy applying my quantitative skills to new large-scale, data-intensive problems.I am an avid learner keen to be the frontrunner in the field of AI. I enjoy learning new technologies at work and strive hard to acquire finesse in skills that I have honed over my career.

    Trained 5000+ participants in R, Machine Learning, Tableau and Python, Big Data Analytics and Deep Learning at Dimensionless

    Conducted workshops and training on Data Analytics for Corporate and Colleges

    He possesses knowledge of a wide variety of machine learning and deep learning algorithms.

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    Pranali is a professional Data Science Trainer with more than 15 years of experience in the teaching various training programs on Databases, Programing and Machine Learning.
    Her core competency include Databases, Data Science and Big Data. She holds a Masters degree in Computer Engineering from University of Pune.


    Are there any pre-requisites to learn this course?

    • Yes, the participant should have a working knowledge of Python for Data Science and must have worked on Machine Learning Algorithms.

    Why Should I Learn Artificial Intelligence from Dimensionless?

    • Dimensionless Tech provides best online data science training that provides in-depth course coverage, case study based learning, entirely Hands-on driven sessions with Personalised attention for every participant. We guarantee Learning.

    What Are The Various Modes Of Training That you Offer?

    • We provide only instructor led LIVE online training sessions. We do not provide classroom trainings.

    How is your online training better than other online or classroom training?

    • In physical classrooms, students generally feel hesitant to ask questions. Unlike other online courses,  we allow you to speak in the session and clarify your doubts. The interactivity level is similar to classroom training and you get it in the comfort of your home. If you miss any class or didn’t understand some concepts, you can’t go through the class again. However, in online courses, it’s possible to do that. We share the recordings of all our classes after each class with the student. Also, there’s no hassle of long distance commuting and disrupting your schedule.

    Can I ask my doubts during the session?

    • All participants are encouraged to speak up and ask their doubts. We answer all the doubts with the same sincerity.

    Where do I get the Softwares from?

    • All the software used in this course are Freely downloadable from the Internet. The trainers help you set it up in your systems. We also provide access to our Cloud-based online lab where these are already installed.

    What is the hardware requirement for this course?

    • Any laptop with 2GB RAM and Windows 7 and above is perfectly fine for this course. For large data, the access will be given on the online lab. 

    What if I miss a session, due to some unavoidable situation?

    • We understand that while balancing your personal and professional commitments you might miss a session. Hence, all our sessions are recorded and the recordings are shared with you through our Learning Management Portal.

    How long will I have access to the Learning Management Portal?

    • You will have lifetime access to the portal and you can view the Videos, Notes, Books, Assignments as many time

    What Kind Of Projects Will I Be Working On As Part Of The Training?

    • During the training you will be solving multiple case studies from different domains. Once the LIVE training is done, you will start implementing your learnings on Real Time Datasets.  You can work on data from various domains like Retail, Manufacturing, Supply Chain, Operations, Telecom, Oil and Gas and many more. You would be working on multiple projects so that you can gain enough content and confidence to enter into the field of Data Science.

    Do You Provide Placement Assistance?

    • Yes, we provide you with real-time industry requirements on a daily basis through our connection in the industry. These requirements generally come through referral channels, hence the probability to get through increases manifold.

      The HR from the team helps you with Resume Building and Interview Preparation as well.

    Do I get a Course Completion Certificate?

    • Yes, we will be issuing a course completion certification to all individuals who successfully complete the training.


    Fake news refers to propaganda, misinformation which is spread via word of mouth, or mainstream media or social media platform.

    The goal is to create a model which characterizes fake news and real news with the help of NLP and deep learning techniques.

    In this project, we will compose our own original music without really knowing any instruments or music by using Deep Learning.

    You will be provided with existing music data and your task is to make a deep learning model that generates new music.

    Image Processing: The dataset given to you contains high-quality photoshopped face images.

    Your task is to make a Deep Learning model that detects whether the face is a real face or a fake face that is either photoshopped or created by AI.

    Your task is to make a model that answers open-ended questions about images using deep learning techniques.

    This project can also be upscaled by adding voice features that can help visually impaired people to get a gist of their surroundings.

    Signature authentication is necessary to avoid forgery of documents in various financial, legal, business and in other environments.

    The aim of is to develop a signature verification system that detects whether the signature is fraud or genuine.

    The COVID-19 pandemic has been spread globally, and the number of cases is rising every day.

    In this project, you have been given world-wide dataset of coronavirus and you have to perform EDA, data analysis and data visualization techniques.

    In this project you have to analyze the Uber dataset and try to find the hidden relationships among time, date, categories, miles, purpose of the drive, start and end location.
    After generating insights, use the data to predict the “travel miles”.

    The goal is to analyse the Zomato Bengaluru dataset to get an understanding of the factors that affect the restaurants in Bengaluru.

    Then you have to predict the “Zomato rate” of the restaurants and perform a sentiment analysis on customer reviews.

    Sentiment analysis measures the attitude and belief of the customer towards the service or product.

    Your task is to make a sentiment analysis model that takes the review of a customer and returns whether the review is positive or negative.

    Accurate forecasting of increasing coronavirus is important. It will help the medical institutions and government to plan their strategies accordingly.

    Your task is to forecast the cumulative number of confirmed COVID-19 cases across the world.

    The task here is to incorporate all the various components of football players and display them in a single environment using clustering, so that users can select their players of interest by one click instead of selecting the features manually.

    Airline companies use techniques to systematically allocate airfare prices. The task given here is to accurately predict the price.

    This will help the passengers to decide a specific airline as per their budget and save their time and money.

    When we order food, questions such as ‘Where is my food?’ or ‘When will my food arrive?’ often emerges in our minds.

    In this project, you will be given data of thousands of restaurants in India and your task is to predict the food delivery time.

    Food quality needs to be assessed from time to time. Your task is to make a ML model that predicts whether a specific facility will pass or fail the food quality assessment, by using the dataset which was collected by the food inspection department.

    Recommendation system broadly recommends products to customers best suited to their tastes and traits.

    Your task in the project is to predict and recommend a few hotels to a user that he/she is more likely to book out of thousands of hotels available.

    Sales Forecasting tells the future sales based on the current and past sales data.

    You are given historical sales data of 45 Walmart stores located in different regions and your task is to predict the weekly sales for each department of every store.


    MNIST Digit Recognition

    MNIST digit is a dataset of 60,000 small square 28×28 pixel.It is classified into the 10 classes using the ANN.

    Fashion MNIST

    Fashion-MNIST dataset consists of the images of fashion articles that are classified into their classes.

    Movie Reviews Sentiment Analysis

    Analyse a dataset of 25,000 movies reviews from the website IMDB, labeled by sentiment (positive or negative).

    Image Recognition on CIFAR-10

    The CIFAR-10 dataset consists of 60000 32×32 colour images.The dataset is used for computer vision algorithms.

    Image Classification on Flowers Dataset

    CNN is used to classify the flower images in respective class: daisy, tulip, rose, sunflower and dandelion.

    Cats and Dogs classification

    The task is to classify cats and dogs with the help of CNN from 50000 images data set of cats and dogs.

    Cards Recognition and Detection

    The dataset consists of different images from a deck. Goal is to identify the card and detect the image.

    Movie Recommendation

    Analysis is to be done to answer different questions about the recommendation of the movies from MovieLens data.

    Real Estate Price Prediction

    Predict the price of homes from a housing dataset with explanatory variables describing homes in Ames.

    Start-up Success Rate and Investment Analysis

    Data analysis can be carried out to identify factors that contribute towards the success of a start-up.

    Insurance Premium Analysis

    The Health Insurance company’s data need to be analyzed to identify factors that lead to less medical charges.

    Consumer Goods Sales Forecast

    Sales analytics is the process used to identify model, understand and predict sales trends and results.

    Automobile Price Analysis

    Automobile data involved analyzing factors that affect the price of automobile by using various information.

    App Market Analysis

    Insights can be drawn for developers to work on and capture the Android market by Play store app data.

    Analysing Flight Operations

    Various data manipulation operations can be performed to get insights about the flights schedule, status, etc.

    California Housing Price

    Aim of the project is to predict the housing prices for a district from the 1990 California Census dataset.

    Health Care Quality Assessment

    Dataset consists of the claims data for the insured patients to predict the quality of healthcare received.

    Baseball Players

    The task is to predict the salary of baseball players playing in major leagues from the StatLib Dataset.

    Heart Disease

    The aim is to identify trends in heart data to predict cardiovascular events that can lead to heart disease.

    Movies Recommendation

    The aim is to build a movie recommendation system based on genres. The data used is gathered from MovieLens.

    Automobile Sales classification

    The project is to predicts monthly sales of the Hyundai Elantra in the United States from the given dataset.

    Framingham Heart Study

    The data of Framingham Heart Study is a cardiovascular cohort study used to predict and prevent heart disease.

    Mall Customer Segmentation

    The Mall Customers data set have information of customer that can be used to carry out customer segmentation.

    Credit Risk Modelling

    The task is to identify if a person will be able to pay/default the loan amount from the loan dataset.


    Machine Learning Specialization

    Duration: 60 hours

    Deep Learning

    Duration: 60 hours