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MAIN LANGUAGES & PLATFORMS THAT YOU WILL LEARN TO BECOME A TOP ML / AI DEVELOPER

Key Program Highlights

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Batch Starts:

Batch 1 - 30th Oct 2018

Batch 2 - 09th Jan 2019

Batch 3 - 26 Mar 2019

Duration:

11 Months

Effort:

7-10 Hours per week

(recommended)

Certification:

Post Graduate Diploma in Machine Learning & Artificial Intelligence (PGD-ML&AI) awarded by Amity University

Fees:

Rs. 135000/- (All-Inclusive)

Options Available - One Time Payment, Cardless EMI Payment

Program Format:

Online + Optional Campus Sessions

UNIQUE FEATURES:

  • 1-1 Mentoring
  • Industry-driven comprehensive curriculum
  • 24/7 access to study material & video lectures
  • Live interactions with Machine Learning experts and Corporate leaders
  • Real-world Projects & Case Studies
  • Capstone ML & AI Project
  • Career guidance and support
  • Get Alumni Status from Amity University

About Us

    • Asia’s No. 1 online education platform
    • Ruling in the area of online education for more than two decades
    • Only internationally accredited online university with over 200,000 international students across 135 countries
    • Most preferred online degree by employers and recruiters across the globe

Program Overview

  • Why Study Machine Learning & Artificial Intelligence?
    • Ranked #6 in the list of highest-paid jobs in 2018 by Report of Economic Times.
    • According to a study, employers’ demand for AI talents has more than doubled over the past three years and the number of jobs has increased by 119%.
    • Finding and attracting talented ML & AI professionals has become a strategic imperative for every company.
    • As India is heading towards Digital India initiative, the IT industry has an increased demand for workforce equipped with ML & AI skills.
    • Knowledge and experience using cutting-edge ML technologies makes you unleash the next wave of digital disruption.
    • Prepares you for the roles of tomorrow and confidently deploy ML & AI applications at your workplace.
  • How will PGD-ML&AI help you?
    • You learn from robust pool of faculty who have worked extensively in projects across Facebook, Google, HP, HT Media, AuthBridge, DRDO, Dell EMC, IHS Markit.
    • You master essential concepts and exceptional skills to train intelligent machines and AI systems effectively.
    • You develop competitive intelligence and industry-driven expertise of utilizing and applying ML techniques and AI systems.
    • You gain a well-rounded foundation and deeper understanding to create solutions for the problems posed by ML & AI.
    • You acquire the required technical skills to develop a verified portfolio of industry projects.
    • You attain practical mastery over a wide range of ML applications in healthcare, retail, financial services and manufacturing industries.

Program Structure & Format

Candidates can complete the 11-months course of study through:
  • Recorded video lectures and other study material from faculty with real-world expertise
  • Optional contact sessions at Amity Campuses with industry mentors and experts to solve queries and doubts
  • Online coursework that includes case studies, mini-projects and assignments
  • Capstone ML&AI Project to work on practical cases
  • Instructor-led practice sessions to learn popular platforms & languages and work on 4 projects during the program
Our Campuses for Contact Classes

  • Amity Bangalore, Kormangala

  • Amity Chennai, Gopalapuram

  • Amity Hyderabad, Punjagutta

  • Amity Mumbai, Malad & Kurla

  • Amity Pune, Senapati Bapat Road

  • Amity Noida, Sector 125

  • Amity Dubai, UAE

  • Amity Singapore, 3 Kay Siang Road

If the contact classes are not available in your city, don’t worry. You will be provided access to the recorded lectures of contact sessions of another nearby city.

Eligibility & Selection

    • Working professionals in IT / Analytics / Statistics / Big Data / Machine Learning
    • Entrepreneurs looking forward to create new products or services in the ML&AI space
    • Fresh graduates from Engineering / Mathematics / IT background
    • Final year students completing their graduation on or before April 2019
    • BE / B.Tech / BCA / MCA / B.Sc. (Maths) / M.Sc (Maths) with a minimum of 50% aggregate marks is compulsory.
    • Minimum of two years full-time work experience after graduation or post-graduation is required.
    • For meritorious fresher students / Young Professionals (CGPA > 7/10), the work experience is relaxed basis on application.

Faculty

Our team of world-class faculties have years of experience as professional trainers and have worked closely with ML & AI adopters across various sectors. Their industry exposure will help you to understand the everyday nitty-gritty to debut as a successful ML & AI professional.

Ashish Gilotra

  • Program Director
  • 20+ Years of Experience in Machine Learning
  • ME - BITS Pilani - Software Engineering
  • Ex, Head ML & AI (HT Media), VP - AuthBridge

NAVEEN BHANSALI

  • Alumni - IIM Bangalore
  • Data Analyst - Dell EMC
  • Ex Engineering - Infosys

DR. SURESH VARADARAJAN

  • 26+ Years of Experience
  • PhD, Engineering - Marquette University
  • BE, IISc Bangalore | MTech, IIT Kanpur

Dr. Sakshi Babbar

  • PhD - Data Mining - University of Sydney, Australia
  • Worked on Predicting Water Quality Index of Yamuna River
  • 14 Years experience in Education

Avinash Gaur

  • Machine Learning Engineering
  • Expert in Applied Statistics
  • Ex-HCL

Course Curriculum 11 Months | 6 Modules

  • Module I – Introduction
    • What is Machine Learning (Definitions - Theoretical, Applied Practice)
    • What is Artificial Intelligence (Definitions - Theoretical, Applied Practice)
    • Machine Learning vs AI
    • Machine Learning vs Deep Learning
    • What makes Machine Learning tick (Algorithms - History, Authors, Purpose or Objective, Learning Style Algorithm, Similarity Style Algorithm, Number of Algorithms, Infographic, Top 10/Most Common ML Algorithms)
    • Types of Machine Learning (Supervised, Unsupervised, Reinforcement)
    • General Steps or Process of Machine Learning (SourceX ->Feature Extraction ->Feature Correlation ->Feature TransformX ->Train Model ->Ensemble ->Evaluate; Data cleaning, data transform/fitting; Overfitting, Underfitting, Variance, Bias)
    • Required Maths (Linear Algebra - In Numpy, Probability, Stats, Calculus)
    • Tool Kit (Python Basics; Python Advance - Numpy, Pandas, Matplotlib; Scikit-learn or sklearn Library)
  • Module II – Supervised Learning
    • Linear Regression
      1. Introduction
      2. Terminology & Assumptions
      3. Use cases
    • Multiple Linear Regression
    • Logistic Regression
    • Hypothesis Testing
    • Odds vs Probability
    • Data and data distribution
      1. Introduction to data preprocessing
      2. Data Transformation & Reduction
      3. data Visualisation
    • Multivariate Analysis
    • Introduction tClassification
    • Supervised Algorithms
    • Under fit and Over fit, Hold out and Cross Validation
    • KNN
    • Naïve Bayes
    • Decision Trees
    • Support Vector Machines
    • Random Forest Technique
  • Module III – Unsupervised Learning
    • Clustering (K-Means, K Nearest Neighbours, Association Rule Learning)
    • Dimensionality Reduction (PCA, SVD, tSNE)
    • Case Study (Clustering/Anomaly/Fraud Detection)
  • Module IV – Reinforcement Learning
    • Markov Decision
    • Monte Carlo Prediction
    • Case Study (next best offer, dynamic pricing)
  • Module V – Neural Networks, Natural Language Processing, Predictive Analytics, Ensemble Techniques
    • Neural Networks/Deep Learning (CNN, RNN/LSTM/GRU, Transfer Learning, Case Study
    • Natural Language Processing (Text Mining, Generation, Case Study)
    • Predictive Analytics - Forecasting (Logistic, Time Series - ARIMA, Case Study)
    • Ensemble Techniques (Boosting, Bagging)
  • Module VI – Machine Learning Applications Across Industries
    • Machine Learning Applications Across Industries (Healthcare, Retail, Financial Services, Manufacturing, Hospitality)
    • Cloud Based ML offerings
    • Top 10 AI Startups
    • Flashcards (Tips, Tricks, Definitions)

Case Studies

Case 1

Breaking Barriers: Micro-Mortgage Analytics

Case 2

Demand Forecasting for Perishable Short Shelf Life Home Made Food at iD Fresh Food

Case 3

Improving Customer Engagement at VMWare through Analytics

Case 4

Larsen and Toubro: Spare Parts Forecasting

Course Expectations

How will your Course look like:
download detailed syllabus

You will receive the download link in your email.

Application Process

  • 1. Fill up the Application Form

  • 2. Screening call from Admission Director's Office basis on Profile

  • 3. Final Application to be shared with Admission Committee for final selection

Program Fees

Rs. 135000 /- (All-Inclusive)

  • One Time Payment

    Rs. 135000/-
    (All-Inclusive)

    • Zest No Interest EMI Option
    • Faster payment with Credit Card, Debit Card, Net Banking

  • Cardless EMI Payment

     

    • Pay Hassle free Zero percent EMI in 12 months.
    • No Credit Card required

Learning Outcomes

By the end of the PGD-ML&AI program, you will be able to:
  • Spearhead Machine Learning models and uncover hidden insights to problems that were once thought impossible
  • Become a leader in the booming market of ML & AI by learning about its breakthroughs achieved and future that it holds
  • Gain solid awareness of the key concepts of AI, ML, Deep Learning, Data Mining & Data Science
  • Make strategically important decisions in your professional domain with ML techniques, models and various algorithms
  • Leverage your innovative ability to develop intelligent ML & AI-based solutions using the required platforms and languages

Certification

Earn a Certificate of Post Graduate Diploma in Machine Learning & Artificial Intelligence (PGD-ML&AI) from Amity University

Add the certificate to your CV and improve your job / business prospects

Case Studies & Assignments

  • Case Studies
    • Get hands-on experience with real-life case studies published by IIM, Bangalore
    • Build a portfolio of demonstrable work by referring to these cases published at Harvard Business Publishing’s case portal
  • Assignments
    • Uncover opportunities to think and learn about ideas & topics and ask questions
    • Submit assignments at the end of each module and know how to apply the concepts to new problems, master the basics and develop intelligent applications
    • Assess your progress with grade/score of each assignment that contributes to the overall grade

Projects & Quizzes

  • Capstone Project
    • Capstone Project - the main highlight of PGD-ML&AI
    • Get an opportunity to solidify the concepts and apply tools & languages learnt in the program on real-world machine learning problems
    • Have access to continuous guidance from a Project Mentor to execute the project
    • Submit a detailed report along with a recorded presentation to achieve success in the project
  • Online Quiz
    • Be responsible for your learning with optional online quizzes at the end of each module
    • Test your subject understanding and improve your programming skills

Evaluation

Class performance will be based on following components:

  • ML & AI projects across various domains
  • Capstone Project
  • Module-based Assignments
  • Quizzes

Faculty members may choose a few or all above stated components.

Career Paths

ML Developer

As a ML Developer, you will be able to:

  • Possess better skills to pre-process data
  • Understand features of data
  • Try multiple algorithms
  • Develop machine learning pipeline
  • Produce and implement accurate models
  • Develop predictions from real-life data
ML & AI Consultant

As a ML & AI Consultant, you will be able to:

  • Spot the areas of application of ML within the organization
  • Develop business insights
  • Forecast models that use most suited ML algorithms
  • Assist business processes
  • Uncover data-driven approaches to help arrive at business strategy

Career Assistance

  • Enhance your career aspirations with assistance from our recruitment partners, Virtual Job Fair and existing Corporate and Alumni network.
  • On successful completion of the program, equip yourself with sophisticated expertise to apply for jobs in the roles of Machine Learning Developer, Deep Learning Engineer, Data Mining Engineer and AI & Machine Learning Consultant in industries like IT, Retail, Healthcare, Telecom, Insurance, Hospitality and FMCG.
  • Get connected with our Career Counsellor towards the end of the program to be interview-ready as per the current industry requirements.

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