Become a Data Scientist – Job training (beginner – advanced)

Become a Data Scientist – Job training (beginner – advanced), available at $19.99, with 10 lectures, and has 3 subscribers.

You will learn about Introduction to the field of Data Science How to build a Data Scientist's mindset Data Science approach Supervised Models: Regression Supervised Learning Models: Classification Various types of classification models for binary and multi-class classification Performance metrics: Confusion Matrix, F1, Precision, Recall, Accuracy – which one to use in which case, with examples Unsupervised Learning: Clustering, performance metrics Model Improvement Methods What does model improvement mean? What are the different options at our disposal and when to use them? Feature Selection and Dimensionality reduction methods: Lasso Regression, Ridge Regression, PCA Hyperparameter Tuning: Various methods, deep dive into Grid-search and Random-search Cross-Validation Application to hyperparameter tuning Introduction NLP with various common NLP tasks How is Natural Language data different from Panel or Tabular Data? Steps for processing natural language inputs: NLP pipeline (Tokenisation, Stopword Removal, Stemming, Lemmatisation) Various methods of word embedding: Bag of Words, Word2vec, Glove, and using Large Language Models Brief introduction to Recurrent Neural Networks and Long Short Term Memory models, the building blocks for all LLMs Pre-trained models and transfer learning This course is ideal for individuals who are Jobseekers or Aspiring Data Analysts or Entrepreneurs or Non tech candidates or Students in any domain or Career change aspirants It is particularly useful for Jobseekers or Aspiring Data Analysts or Entrepreneurs or Non tech candidates or Students in any domain or Career change aspirants.

Enroll now: Become a Data Scientist – Job training (beginner – advanced)

Summary

Title: Become a Data Scientist – Job training (beginner – advanced)

Price: $19.99

Number of Lectures: 10

Number of Published Lectures: 10

Number of Curriculum Items: 10

Number of Published Curriculum Objects: 10

Original Price: $99.99

Quality Status: approved

Status: Live

What You Will Learn

Introduction to the field of Data Science
How to build a Data Scientist's mindset
Data Science approach
Supervised Models: Regression
Supervised Learning Models: Classification
Various types of classification models for binary and multi-class classification
Performance metrics: Confusion Matrix, F1, Precision, Recall, Accuracy – which one to use in which case, with examples
Unsupervised Learning: Clustering, performance metrics
Model Improvement Methods
What does model improvement mean? What are the different options at our disposal and when to use them?
Feature Selection and Dimensionality reduction methods: Lasso Regression, Ridge Regression, PCA
Hyperparameter Tuning: Various methods, deep dive into Grid-search and Random-search
Cross-Validation
Application to hyperparameter tuning
Introduction NLP with various common NLP tasks
How is Natural Language data different from Panel or Tabular Data?
Steps for processing natural language inputs: NLP pipeline (Tokenisation, Stopword Removal, Stemming, Lemmatisation)
Various methods of word embedding: Bag of Words, Word2vec, Glove, and using Large Language Models
Brief introduction to Recurrent Neural Networks and Long Short Term Memory models, the building blocks for all LLMs
Pre-trained models and transfer learning

Who Should Attend

Jobseekers
Aspiring Data Analysts
Entrepreneurs
Non tech candidates
Students in any domain
Career change aspirants

Target Audiences

Jobseekers
Aspiring Data Analysts
Entrepreneurs
Non tech candidates
Students in any domain
Career change aspirants

Welcome to ‘Data Scientist – Job training‘, a first-of-its kind short program designed for jobseekers and career change aspirants.

This course is specifically created as a JOB-BASED TRAINING program thereby teaching concepts hands-on and relevant to real-work environment. If you are looking for a job in Data Science or if you are a student who would like to get first experience in this domain, this course is exactly for you.

How is this program a JOB-BASED TRAININGand how will it equip you with skills relevant for your role:

What companies ask for a Data Scientist role?

Gather and clean large datasets from diverse sources to ensure data accuracy and completeness.
Collaborate with cross-functional teams to understand data requirements and optimize data collection processes.
Conduct exploratory data analysis to identify patterns, trends, and anomalies.
Design and implement machine learning models for predictive and prescriptive analytics.
Develop and engineer relevant features to improve model performance and accuracy.
Evaluate model performances
Stay informed about the latest advancements in machine learning and data science techniques.

How this course meets the requirements?

Learn about Data Loading and EDA
Collaborate with team members on various tasks and on Kaggle
Gain knowledge on EDA and Data Insight generation
Understand the concepts of feature engineering, feature selection, baseline model building, model performance analysis and model metrics
Learn about hyperparameter tuning, comparison of models, grid search, cross-validation
Learn and evaluate model performance and compare various models
Get introduced to NLP and advancements in Data Science

Tools you will learn:

Pandas
Numpy functions
Python functions
Kaggle notebooks
Google colab
matplotlib
seaborn
nltk
Scikit learn
XGBoost
LightGBM
Transformers, and many more ML packages and libraries, model metrics: cross entropy, DB Index, etc. NLP, and LLMs for ML tasks (hugging face library)

Extra Module and Benefits:

1. AI Fundamentals and Applications:

Unlock exclusive access to one of our AI modules Learn from our experts leveraging AI to enhance your productivity and understand the wide variety of applications of AI across industries

2. Career Guidance

Understand how to effectively search for a job, find startups, craft a compelling CV and Cover Letter, types of job platforms and many more!

Trainers:

Dr. Chetana Didugu – Germany

Dr. Chetana Didugu is an Experienced Data Scientist, Product Expert, and PhD graduate from IIM Ahmedabad. She has worked 10+ years in various top companies in the world like Amazon, FLIX, Zalando, HCL, etc in topics like Data Analysis and Visualisation, Business Analysis, Product Management, Product Analytics & Data Science. She has trained more than 100 students in this domain till date.

Aravinth Palaniswamy – Germany

Founder of 2 startups in Germany and India, Technology Consultant, and Chief Product Officer of Moyyn, and has 10+ years of experience in Venture Building, Product and Growth Marketing.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Data Scientist Workshop

Lecture 2: Introduction to Data Science (contd)

Lecture 3: Supervised learning

Lecture 4: Unsupervised learning

Lecture 5: Hyperparameter tuning

Chapter 2: Career Guidance

Lecture 1: How to search for jobs effectively?

Lecture 2: How to write a good CV and Cover Letter?

Chapter 3: AI applications

Lecture 1: Part 1

Lecture 2: Part 2

Chapter 4: Bonus

Lecture 1: Bonus

Instructors

GATE by Moyyn
Training talent on next-generation skills

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Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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