Advance Machine Learning-Deep Learning Certification Program

  16 Weeks Lectures with Mini Projects
  4 Weeks E2E Industry Projects & Case Studies


  Batch Start Date Timings
   Batch-1 29-Feb'20 6:00 PM - 8:00 PM

Download program brochure


"AI will add 2.3 million jobs by 2020"~ Gartner
Program Features

    "Artificial Intelligence is the New Electricity" ~ Andrew Ng

    Technology giants are rapidly migrating to an AI-ML world. The industry is getting disrupted. It is very obvious where tomorrow’s jobs are going to be. Upgrading your expertise in AI/ML is the best way to sustain your career growth and professional stability.
  • Instructor led Live Online Course.
  • Training Certificate
  • Course mentored by Industry Machine Learning experts
  • Program is designed by industry experts having over a decade of working experience with niche companies and giving solutions to complex industry problems.
  • Advanced machine learning and artificial intelligence concepts such as Deep Learning, Neural Networks, Natural Language Processing and Computer Vision.
  • Learn cutting-edge applications through projects created with the industry experts: Chat Bots, Image Classifiers and much more.
  • Apply for suitable Data Science, Machine Learning and AI profiles and you will get expert mentorship which will help you prepare for best of the industry jobs.
  • This course covers every bit of Mathematics, Statistics & Computer Science working behind complex algorithms and its applications.
Program Mentors
Ajay Sir from Oracle with 14+ years of industry experience
Gaurav Sir from BITS Pilani with 14+ years of industry experience
Who should take this course?
  • Entry level working professionals who are looking to build a career in Data Science and Machine Learning.
  • All students who want to learn Advance Machine Learning and start career in the most exciting & highest paid technology in the industry.
  • Engineering students B.Tech/BE ( Any Branch )
  • Postgraduate students MCA,MBA, PGDBM etc.
Program Details:
  • Registration OPEN for Feb'20 batch starting from:
    29-Feb'20 , 6:00 PM-8:00 PM IST
  • Take first weekend classes as FREE TRIAL Class and experience the wonderful journey in to the world of Machine Learning.
  • Program Duration : 16 Weeks Classroom Lectures with Mini Projects
    4 Weeks: E2E Industry Project at Kaggle
  • Course Schedule : Classes would be conducted on Weekend (Sat & Sun)
Registration Process
  • Register for Program (Make sure all the details given are correct).
  • Registration confirmation will be sent by an automatic mail.
  • Online session details to join classes will be shared on registred mail id TWO days before starting of the program.
  • We offer first 2 classes as DEMO Class to make you feel the magical world of AI.
  • Student have to deposit the course fee after completion of first week demo classes.
Explore Program
Machine Learning Foundation
  • Python for Data Analysis: Get acquainted with Data structures, Object Oriented Programming, Data Manipulation and Data Visualization in Python.
  • Mathematics for Machine learning:
  • -Linear Algebra
  • -Multivariate calculus
  • -Probability theory and Probability Distributions
  • -Matrices, Eigen Vectors and their application for Data Analysis.
  • Computer Science & Algorithms: Matrix implementation/ Data Structures & Algorithms
  • Introduction to Cloud Computing and AWS
  • Functions and Graphs
  • Statistics and it's applications
  • Hypothesis Testing
  • What is Machine Learning – Examples and Applications
  • Numpy and Pandas Tutorial
  • Scikit Learn Tutorial
  • Machine Learning Algorithms
  • Cost Function
  • Metrics for Model Evaluation and Validation
  • Training and Testing
  • Model Overfitting-Underfitting
  • Bias & Variance
  • Gradient Descent Optimization & Learning Rate
  • Bias & Variance
  • Hyperparameters Tuning & Model Optimization
  • S2 Mini-Projects to understand and implement Machine Learning Basics
  • Data Wrangling
  • Data Pre-processing
  • Feature Selection
  • Feature Transformations
  • Outlier Detection and Handling
  • Handling Missing Values
  • Introduction to Supervised Learning
  • Linear Regression
  • Logistic Regression
  • Decision Trees
  • Random Forests
  • Naïve Bayes Classifier
  • Bayesian Statistics and Inference
  • K-Nearest Neighbor
  • Support Vector Machine - SVM
  • One mini project hands-on for each algorithm
  • Introduction to Unsupervised Learning
  • K-Means Clustering
  • Agglomerative Hierarchal Clustering
  • Clustering using DBSCAN
  • Expectation–Maximization (EM) Clustering using Gaussian Mixture Models (GMM)
  • Clustering Mini-Project
  • Machine Learning on Google Colab/li>
  • Introduction to Deep Learning
  • Machine Learning VS Deep Learning
  • Introduction to Neural Networks
  • TensorFlow/Theano/Keras
  • Deep Neural networks
  • Forward propagation
  • Back Propagation Learning
  • Activation Functions
  • Loss Functions
  • Hyperparameter Tuning
  • DropOut Regularization
  • Batch Normalization
  • Early Stopping
  • Vanishing & Exploding Gradient Descent
  • Optimization Algorithms
  • - Gradient descent with momentum
  • - RMS Prop
  • - Adam
  • Introduction to Computer Vision
  • Convolutional Neural Networks CNN
  • Residual Netoworks- ResNets
  • Long Short Term Memory LSTM
  • Case Studies
  • - Le-Net5
  • - AlexNet
  • - VGG16
  • - Google Net( Inception Networks)
  • Transfer learning
  • Data Augmentation - Keras Generators
  • Face Recognition
  • Kaggle Project on Computer Vision
  • Introduction to Natural language Processing
  • Application of NLP
  • NLTK
  • Tokenization
  • Stemming
  • Lemmatization
  • Stop Words
  • Similarity Functions - TFIDF
  • Word Representations
  • One Hot Encoding
  • Word Embedding
  • Learning word Embedding
  • - Word2Vec
  • - SkipGram , N-Gram
  • - Negtaive Sampling
  • - GloVe
  • Recurrent Neural Netoworks- RNN
  • BiDirectional RNN
  • Gated Recurrent Unit GRU
  • Long Short Term Memory LSTM
  • Kaggle Project on NLP
  • PCA
  • LDA
  • Kernel PCA
  • k-fold Cross Validation
  • Grid Search
  • Bagging
  • ADA boost
  • XGBoost
  • Light GBM
  • Ensembling Techniques
  • Stacking
  • All ML/DL algorithms will be covered with hands-on mini projects
  • 15-20 mini projects
  • Deep Learning Projects:-
  • -Sentiment Analysis
  • -Handwritten Digits recognition
  • -Named Entity Recognition using Deep Learning Algorithms
  • -Image Classfication
  • -Mails/Document Classification
  • Hackathons & Competitions
  • Introduction to Kaggle Platform and other Data Science Competitions
  • 8 weeks E2E Kaggle and HackerRank project competitions for PrePlacement and Data Science Job offer.
  • Acing ML Interviews
  • -Booklet of all ML interview questions
  • -Showcasing and presenting ML projects in interviews?
  • -Do's-Dont's in interviews
  • -Interviews preparation
  • Resume Preparation
  • -How to make a impressive resume?
  • -Mention right ML Projects in resume
  • -A good & a Bad resume

Download program brochure

"A breakthrough in machine learning will be worth ten microsoft's"~ Bill Gates
Mentor: Gaurav Sir ( From BITS Pilani, Oracle with 14+ Industry Exp.)
Mentor: Ajay Sir ( From Oracle with 14+ Industry Exp. )


  Duration 12 Weekends
  Pre-requisites Interest in Mathematics
  Batch size 6
  Program starts 29-Feb-20
  Mode Online
  Instructor BITS Pilani
Need More Information,Please Write to Us


Feb'20 batch




Start Date


End Date

4:00 PM-6:00 PM


20 Weeks




2 Hours

Each session





₹ 20,000 ( $ 300 ) ₹ 16,000 ( $ 240 ) inc. Taxes

*Offer valid till 25 Feb'20 11:59 PM

  • Payment Options


    A/C # 916020018356139 , IFSC Code : UTIB0001082
    Bank: Axis Bank | A/C Type: Current
    Send Transaction ID with Name & Phone at

  • Fee Refund Policy

    Course registration is FREE.
    Student need to deposit full fee within 3 days after taking the free demo classes to continue with the course.
    We ensure that you are satisfied with the demo class and want to continue with the program. When student deposit the full fee after the demo class, there will be no refund of any kind.
    Fee is neither refundable nor transferrable.

My Experience at IT Bodhi

Kartik Tyagi
Placed at Grofers as ML Engineer
B.Tech-CS Jaypee Noida College

I did my Machine Learning Training from IT Bodhi. I can bet you that IT Bodhi is the best machine learning training institute in Delhi NCR. It is the best course for beginners as well as professionals who wants to dig deep into the algorithms and concepts of Machine Learning. Ajay Sir and Rajnish Sir are the best trainers who helped me on live projects. I am truly grateful to IT Bodhi for their guidance at every step and it is hard to find mentors like them.

Kuldeep Arya
Placed at Devnagri as ML Engineer
B.Tech-Mechanical from Amity University

I am a Mechanical engineer and wanted to change my domain to ML/Data Science. Initailly learning 'Machine learing' and getting a job in this domian was a distant dream for me. Faculty at IT Bodhi are great mentors and in just 6 months I was able to learn Machine Learning and crack ML job interviews. Great environmnent of learning and support at IT Bodhi. I highly recommend IT Bodhi.

Navya Singh
Placed at TCS-Digital as ML Engineer
B.Tech-CS from Jaypee Noida College

It is hard to find words to express my gratitude to Ajay and Rajnish sir who made Machine Learning so easy to understand with practical implementation. Highly recommended to everyone who want to make career in Data Science and Machine Learning.

Abhishek Jain
Placed at Capgemini
B.Tech-ECE at ABES Engg. College Ghaziabad

Machine Learning was completely new for me and programming was not my cup of tea. I explored many institutes and finally chose IT Bodhi and it came out be the right decision. Now ML is my passion and I am quite a coder in Python. Lot of learning and good projects. Landed up in Capegemini and my journey is just started in to the world of Machine Learning.

Frequently Asked Questions

  • How much time will it take to be a Machine Learning Engineer?

    If you complete this cours in Machine Learning, you will definitely be able to apply and grab entry level data scientist and Machine Learning engineer roles at any product or service level companies.

  • Is this course personalized for me?

    Yes,definitely the course is personalized to each and every individual. In our regular classes, course mentors helps in clearing all the doubts and assignments and full assistance to complete E2E Industry project.

  • Is any specific programming language experience required?

    The Program will use Python libraries. The necessary python skills can be easily picked up by anyone with no or little programming experience. Basic Python classes are part of the program. Self learning material on Python for will also be made available.

  • I am from Non IT/CS Branch, will this program help me to get job in Machine Learning?

    Yes, definitely. After doing our courses, you will have sufficient theoretical knowledge to take machine learning interviews with hands-on experience in E2E industry project. Python is part of the program and Mentor will help you in learning programming basics and gradually you will be profecient in python as course progress. Python is very user friendly language and can be easily learned.

  • What happens if I miss a Class?

    It is recommended that you do not miss a class. In case it is unavoidable we will try to conduct special session or cover in other batch.

  • Will I get a certificate after completion of courses?

    Yes, Certificate will be given at the end of the course.