AI is one of the key skills today. The Saksham AI mentoring program offers an opportunity to learn AI using your coding knowledge. Set up by education experts in the UK, the program has the following highlights

We start three month from Saturday 06 Feb 2021.
The objective is to teach AI (machine learning and deep learning) using coding in Python
We expect the participants to know some coding but not necessarily Python
You will need a laptop and a browser
Team and acknowledgements: Ajit Jaokar + TBC

Module schedules

Feb 1 Introduction to core Python (details below)
March 1 Python libraries (numpy, Pandas, Matplotlib, SKlearn)
April 1: End to End classification and regression problems
Submissions as ipnyb notebook format

Module details

Introduction to Core Python

Notebook interface(Colab)
Variables
Data types
Assignment
Decisions
Functions
Files
Object Oriented Programming

Python libraries for machine learning

numpy

• Creating Arrays

• Accessing Arrays

• Other properties of Arrays

• Performing operations on Arrays

Pandas

• Series

• Dataframes

• Dealing with missing values

• Statistics, Group By

• Feature Engineering, Apply functions

ScikitLearn

• Rescaling and Standardizing data

• Model evaluation and metrics

• Classification and Regression model instantiation

• Regularization

• Optimizing Parameters

• Ensemble models

• Building Pipelines

Matplotlib

• Basic Plots

• Customising plots, subplots

End to End Problems

End-to-End Machine Learning Problem: Regression

Define the Problem Statement
Analyse and Preprocess data
Split the data
Choose a Baseline algorithm
Choose an evaluation metric
Refine our dataset
Split data into train and test

Run baseline model on refined dataset
Test Alternative Models
Choose the best model and optimize its parameters
Use to predict and evaluate

End to End ML Problem: Classification

Define the Problem Statement
Analyze and Preprocess data
Split the data
Choose baseline algorithm
Train and Test the Model
Choose an evaluation metric
Refine our dataset
Test Alternative Models
Choose the best model and optimize its parameters

Team

Ajit Jaokar

Based in London, Ajit's work spans research, entrepreneurship and academia relating to artificial intelligence (AI) and the internet of things (IoT).

He is the course director of the course: Artificial Intelligence: Cloud and Edge Implementations. Besides this, he also conducts the University of Oxford courses: AI for Cybersecurity and Computer Vision.

Ajit works as a Data Scientist through his company feynlabs - focusing on building innovative early stage AI prototypes for domains such as cybersecurity, robotics and healthcare.

Besides the University of Oxford, Ajit has also conducted AI courses in the London School of Economics (LSE), Universidad Politécnica de Madrid (UPM) and as part of the The Future Society at the Harvard Kennedy School of Government.

He is also currently working on a book to teach AI using mathematical foundations at high school level.

Ajit was listed in the top 30 influencers for IoT for 2017 along with Amazon, Bosch, Cisco, Forrester and Gartner by the German insurance company Munich Re.

Ajit publishes extensively on KDnuggets and Data Science Central.

He was recently included in top 16 influencers (Data Science Central), Top 100 blogs (KDnuggets), Top 50 (IoT central), and 19th among the top 50 twitter IoT influencers (IoT Institute).

His PhD research is based on AI and Affective Computing (how AI interprets emotion).

Dr Amita Kapoor

Amita Kapoor is an Associate Professor in the Department of Electronics, SRCASW, University of Delhi, and has been actively teaching neural networks and artificial intelligence for over twenty years, and she is an active member of ACM, AAAI, IEEE, and INNS.

Amita completed her masters in Electronics in 1996 and her Ph.D. in 2011.

During her Ph.D she was awarded a prestigious DAAD fellowship to pursue a part of her research work in Karlsruhe Institute of Technology, Karlsruhe, Germany. Amita was awarded the Best Presentation Award at the Photonics 2008 international conference.

Amita has more than 50 research publications in international journals and conferences, and has co-authored four books, including the best-selling “Deep learning with TensorFlow2 and Keras” with Packt Publications.

Passionate about using her skills for the betterment of society and humankind, Amita spends her spare time in various AI-related IoT and healthcare open source projects. She was recently awarded the Intel AI Spotlight Award 2019 for her work on the early detection of Acute Myeloid Leukemia using AI.

Amita’s present research areas include Machine Learning, Artificial Intelligence, IoT, Deep Reinforcement Learning, and Robotics.

Kajal Singh

Kajal is a Machine Learning Engineer working with Machine Learning and AI projects for a large global consultancy.

She has worked on use cases like anomaly detection, sentiment analysis, classification, transactional AI assistants, complex big data processing, data analytics, document digitisation etc. Kajal also has been a part of multiple hackathons conducted within and across IT industries.

She is also awarded with Amazon Pride Card for her research contribution to “Women In AI” project of IIIT, Bangalore

She has won special recognition for her project 'Transactional AI assistant'. She also has been honoured as 'Master Hacker' in Makeathon at a regional level in India.

Kajal has also been leading a research project (non-commercial) working with a German company on pricing optimization using Reinforcement Learning (RL).

Her project involves working on RL on pricing optimisation strategy for revenue increase and customer retention using a mixture of algorithms based on Markov Decision Processes (MDP).

Aditya Jaokar

Aditya Jaokar is a student of Computer Science in London. He will be responsible for the development and evaluation of the coding submissions

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