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Complete Machine Learning Mastery - Curriculum

Build hands-on Data Science / AI skills from practicing Data scientists, solve industry grade DS projects with real world companies data and get certified. Go from Zero to Job ready in 12 months.

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Program Highlights

  • No Pre-requisites
  • Work on real data from companies
  • Industry vetted curriculum
  • One-on-One Mentor support
  • 24X7 Query Resolution
  • Build Portfolio
  • Course Completion Certificate

Case Studies

and 30+ more case studies...

Course Curriculum

Month 1: Coding for Data Science

  • Foundations of Machine Learning Lessons: 28 Tasks: 05
  • Python Programming Lessons: 50 Tasks: 10
  • SQL for Data Science - Level I Lessons: 2 Tasks: 4
  • SQL for Data Science - Level II Lessons: 26 Tasks: 3
  • SQL for Data Science - Level III Lessons: 13 Tasks: 2
  • SQL for Data Science - Window Functions Lessons: 8 Tasks: 2
  • Numpy Library Lessons: 29 Tasks: 05
  • Pandas Library Lessons: 84 Tasks: 16

Month 2 & 3: Machine Learning

  • Linear Algebra for Machine Learning Lessons: 19 Tasks: 1
  • Statistics for Data Science Lessons: 28 Task: 01
  • Exploratory Data Analysis (EDA) Lessons: 98 Tasks: 18
  • Linear Regression and Regularisation Lessons: 54 Tasks: 10
  • Classification: Logistic Regression Lessons: 35 Tasks: 06
  • Imbalanced Classification Lessons: 25 Tasks: 04
  • Supervised Algorithms Lessons: 57 Tasks: 10
  • Ensemble Learning Lessons: 20 Tasks: 04

Month 4 Deployment/Productionization of AI applications

  • Launch app in AWS EC2 Lessons: 19 Tasks: 02
  • Launch app in AWS Lambda Lessons: 09 Task: 02
  • Launch app in AWS Sagemaker Lessons: 09 Tasks: 02
  • PySpark for Data Science - I: Fundamentals Lessons: 24 Tasks: 02
  • PySpark for Data Science - II: Statistics for Big Data Lessons: 22 Tasks: 02
  • PySpark for Data Science - III: Data Cleaning and Analysis Methods Lessons: 21 Tasks: 04
  • PySpark for Data Science - IV: Machine Learning Lessons: 25 Tasks: 01
  • PySpark for Data Science - V: ML Piplines Lessons: 17 Tasks: 01

Month 5: Time Series Forecasting

  • Time Series Forecasting Lessons: 31 Task: 06
  • Time Series Analysis Part 1 Lessons: 02 Task: 01
  • Time Series Analysis Part 2 Lessons: 02 Task: 01
  • Time Series Forecasting - Statistical Models Lessons: 15 Task: 01
  • Time Series Forecasting - Complete ARIMA Modeling and Tests Lessons: 15 Task: 01
  • Deep Dive into Multi Time Series Forecasting - Vector Auto Regression Lessons: 20 Task: 01
  • Time Series Forecasting - Singular Spectrum Analysis Lessons: 18 Task: 01
  • Feature Engineering and Intervention Analysis for Time Series Projects - Part 1 Lessons: 17 Task: 01
  • Feature Engineering and Intervention Analysis for Time Series Projects - Part 2 Lessons: 16 Task: 01

Month 6: Industry Projects in Machine Learning

  • Estimating Customer Lifetime Value Lessons: 31 Tasks: 06
  • Microsoft Malware Detection Project Lessons: 41 Tasks: 08
  • Credit Card Fraud Detection Lessons: 51 Tasks: 10
  • Restaurant Visitor Forecasting Lessons: 57 Tasks: 10

  • Optimizing marketing spend using Market Mix Modeling (MMM) Lessons: 35 Tasks: 06
  • Predict Rating given Amazon Product Reviews using NLP Lessons: 25 Tasks: 04
  • Uplift Modeling: Estimating Incremental Impact of Marketing Campaigns Lessons: 11 Tasks: 01
  • Uplift Modeling Part 2: Modeling Strategies Lessons: 18 Tasks: 02
  • Survival Analysis: Predicting Time to Event in real world applications Lessons: 16 Tasks: 01
  • Survival Analysis: Predicting Time to Event for Lungs Cancer Patients Lessons: 14 Tasks: 01
  • Attribution Models in Marketing Lessons: 18 Tasks: 01
  • Dynamic Pricing using Multi Armed bandit(Reinforecment learning) Lessons: 14 Tasks: 01
  • Reinforcement Learning for Online Ad Serving With Multi Armed Bandits Lessons: 13 Tasks: 01
  • Portfolio Optimiziation of volatile assests: Effecient Frontier- Python Lessons: 15 Tasks: 01

Month 7&8: Deep Learning

  • Foundations of Deep Learning Lessons: 18 Tasks: 02
  • Foundations of Deep Learning in Python Lessons: 33 Tasks: 06
  • Applied Deep Learning with PyTorch Lessons: 43 Tasks: 08
  • Computer Vision with Convolutional Neural Networks Lessons: 28 Tasks: 06
  • Sequence Modelling with RNN and LSTMs Lessons: 26 Tasks: 06
  • Advanced Topics in Deep Learning Lessons: 42 Tasks: 08

Month 9&10: Deep Learning Projects

  • Project 1: Detecting Defects in Steel Sheets with Computer Vision Lessons: 24 Tasks: 04
  • Project 2: Text Generation using Language Models with LSTM Lessons: 15 Tasks: 02
  • Project 3: Classifying Sentiment of Reviews using BERT (NLP) Lessons: 20 Tasks: 04

Know your Guides

Primary Instructor
Selva Prabhakaran

Hi everyone, I’m Selva Prabhakaran, Your instructor
I am super excited to mentor you on this project!

I head the Data Science team for a global Fortune 500 company and over the last 10 years of my data science experience I’ve deployed 20+ global products. I’m also the Founder & Chief Author of Machine Learning Plus, which has over 4M annual readers.

I specialize in covering the in-depth intuition and maths of any concept or algorithm. And based on my existing student requests, I’ve put up the series of courses and projects with detailed explanations – just like an on the job experience. Hope you love it!

Selva Prabhakaran
Principal Data Scientist
Program Advisors
Program Adviser Picture
Sriram Krishnamoorthy
Assistant Professor | UC Santa Barbara | Ex Ohio State University

Sriram is a seasoned engineer and academician, and has been globally recognized from his publications on technology. He currently serves as the Assistant Professor University of California, Santa Barbara He has been empaneled as the academic advisor for the Data Science Program

Program Adviser Picture
Rajagopal Sathyamurthi
Tech leader, Amazon | ex-CTO | Stanford and BITS Pilani Alum

Rajagopal is a hands-on engineering leader with 8+ years of experience in driving full-stack engineers, data engineers, data scientists and QA engineers across distributed delivery environments. He has been empaneled as the technical advisor for the Data Science Program

Program Adviser Picture
Surya Parameswaran
ML Architect, CredAvenue | Ex DS, Groupon | Rutgers University

Surya is an experienced Data Science leader with a demonstrated history of working in the e-commerce industry. Strong engineering professional skilled in Machine learning. He has been empaneled as the data science advisor for the program

Program Adviser Picture
Wazim Mohammed Ismail
Postdoctoral Fellow Mayo Clinic | Ex-Indian University

Wazim has multiple years of experience in solving computational challenges in genomics. He is known for his research on mutation spectrum analysis in next Gen Sequencing data (BWA, Phylip,Python, Java). He has been empaneled as the statistics advisor for the program

Program Mentors
Program Adviser Picture
Preetam Nayak
Data Science Associate,
Kearney | Ex- Mu-Sigma
Program Adviser Picture
Shraddha Sutar
Data Scientist, Red Hat |
Ex - University of Illinois
Program Adviser Picture
Yerriswamy M
Data Science Consultant,
Accenture | Ex- Philips
Program Adviser Picture
Jayant Raisinghani
Data Scientist, Humana |
University of Texas, Austin University

and 30+ industry experts...

What you'll achieve?

Get Data Science Jobs

Deploy your first AI software

Ideate AI based products

Be able to oversee data science projects

Launch AI business

Crack interviews

Who is this course for?

Data Science Aspirants seeking jobs

Data Science Practitioners looking to hone skills

Professionals who want to switch to Data Science career

Non-Tech Managers who want to oversee DS projects

Leaders who to digitally transform their organization

Entrepreneurs wishing to launch a business in AI space

Verifiable Certificate of Accomplishment

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When You Complete This Course, You get certificate for each of the 30 Courses in Machine Learning Plus University.


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