Data Science Professional Learning Pack

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Data Science Video Lectures
Data Science Video Lectures

This is your opportunity to learn hands-on a wide variety of data science skills at this 1.5-hour online lecture. Your laptop must have Anaconda 3.6 pre-installed before you start learning.

This is your opportunity to learn hands-on a wide variety of data science skills at this 1.5-hour online lecture. Your laptop must have Anaconda 3.6 pre-installed before you start learning.

Why Do Businesses Around The World Still Need More Data Scientists Despite The Covid-19 Pandemic?

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Key Takeaways:

Effects of COVID-19 across industries

How can Data Science help

How long will it be in bloom

How can I make a transition

Open Q&A and Networking

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Key Factors That Help You Get Through In Data Science Hiring

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Key Takeaways:

How do people hire for a Data Scientist role

How to get noticed by recruiters

Who is getting placed

Data Science hiring cheat sheet

Data Science roles in the industry

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How To Make A Career Transition In Data Science :: The Switch From Sales To Data Science

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Key Takeaways:

What is Data Science?

What the market wants?

How to switch careers?

Why do people succeed?

Why do smart people fail?

Open Q&A and Networking

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Data Science at LinkedIn

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Key Takeaways:

Transition from Academics to Business

Importance of Story telling

How to get started

Data Science function

Data Science roles in the industry

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How to build Machine Learning Models using Logistic Regression

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Key Takeaways:

Understand data extraction, exploration and visualization

Learn how to prepare data for ML algorithms

Learn how to train and finetune models

Learn how to deploy into a serialized object for future use

Open Q&A and Networking

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Decision Trees in Machine Learning and its applications

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Key Takeaways:

Learn the intuition behind a decision tree

Learn how to build a decision tree and implement the same in Python

Understand the concept of overfitting

Understand the concept of Ensemble methods

Learn the intuition behind Random Forest

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Clustering Algorithms in Machine Learning and its applications

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Key Takeaways:

Understand your problem framework - Supervised vs. Semi-Supervised vs. Unsupervised Machine Learning

Clustering use cases

Types and working of different Clustering Algorithms

Implementation of clustering in python

The intuition behind clustering analysis

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Use Cases of Random Forrest in Machine Learning

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Key Takeaways:

Data Pre-processing

Feature Engineering

How to model using Linear Regression/Random Forests

Open Q&A and Networking

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Understanding Linear Regression In Machine Learning Easily

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Key Takeaways:

Intuition behind Linear Regression

Implementation of Linear Regression using sklearn

Intuition behind Regularization and its implementation

Open Q&A and Networking

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A Simple Way To Build Your Own Language Model Using NLP

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Key Takeaways:

Understand the field of NLP and an introduction to language models

Different types of language models & Introduction to word embeddings

Building your own language model & Intro to transfer learning in NLP

Use cases of language models

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Introduction To Language Models And NLP

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Key Takeaways:

Understand the field of NLP and an introduction to language models

Different types of language models & Introduction to word embeddings

Building your own language model & Intro to transfer learning in NLP

Use cases of language models

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Classifying Data Using Support Vector Machines (SVM) In Python

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Key Takeaways:

Understand the intuition behind support vectors and SVM

Learn applications of SVM in ML

Understand the workings of SVM

Learn how to implement SVM in Python

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Understanding Boosting

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Key Takeaways:

Intuition behind Boosting

Working of Boosting Models

Understanding of different types of Boosting

Implementation of Boosting using Sklearn and XGBoost

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Understanding Clustering

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Key Takeaways:

Understanding of unsupervised learning methods

Working of Clustering methods

Understanding of unsupervised learning methods

Implementation of Clustering methods

Clustering use cases

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Building Chatbot using Rasa Tech stack

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Key Takeaways:

Understand what chatbots are and their industry use cases

Know the concept behind Natural Language Understanding (NLU)

Learn how conversation flows in a chatbot

Learn how to write your own chatbot from scratch using open source technologies (Rasa Tech Stack)

Understand how to integrate chatbot with web applications

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Data Science Video LecturesData Science Video Lectures

Why Do Businesses Around The World Still Need More Data Scientists Despite The Covid-19 Pandemic?

Key Factors That Help You Get Through In Data Science Hiring

How To Make A Career Transition In Data Science :: The Switch From Sales To Data Science

Data Science at LinkedIn

How to build Machine Learning Models using Logistic Regression

Decision Trees in Machine Learning and its applications

Clustering Algorithms in Machine Learning and its applications

Use Cases of Random Forrest in Machine Learning

Understanding Linear Regression In Machine Learning Easily

A Simple Way To Build Your Own Language Model Using NLP

Introduction To Language Models And NLP

Classifying Data Using Support Vector Machines (SVM) In Python

Understanding Boosting

Understanding Clustering

Building Chatbot using Rasa Tech stack

Data Science Video Lectures
Data Science Video Lectures