Grow Data Skills

Module 1 - Python for Data Science

EDA with Python - Revising Python Libraries
- 📍 Data Mining, Data Cleaning , Data Tranformation and Data Visulaization

EDA with Python - Art of Doing EDA
- 📍 End to End Data Analysis using Python

Module 2 - Statistics for Machine Learning

Descriptive Statistics
- 📍 Measures of Central Tendency, Dispersion
- 📍 Skewness, Kurtosis

Probability & Distributions
- 📍 Probability Theory, Bayes Theorem
- 📍 Probability Distributions, Sampling

Inferential Statistics
- 📍 Confidence Intervals, Hypothesis Testing Basics
- 📍 t-test, ANOVA, Chi-square Tests

Hypothesis Testing and Regression Analysis
- 📍 Linear Regression Assumptions, t-test, F-test, Regression Diagnostics

Getting all stats together plus Practical Use cases

Module 3 - Mathematics for Machine Learning

Linear Algebra Fundamentals
- 📍 Vectors, Matrices, Matrix Operations
- 📍 Eigenvalues, Eigenvectors

Calculus for ML
- 📍 Derivatives, Integrals, Partial Derivatives
- 📍 Gradient, Chain Rule

Optimization Techniques
- 📍 Gradient Descent, Stochastic Gradient Descent
- 📍 Convergence, Learning Rate Tuning

Module 4 - Introduction to Machine Learning

ML Overview & Data Preprocessing
- 📍 Data Cleaning, Feature Scaling, Feature Engineering,What is Machine Learning.

Module 5 - Pre-ML Essentials

Model Evaluation Metrics
- 📍 Accuracy, Precision, Recall, F1 Score, ROC-AUC, Confusion Matrix.

Overfitting & Underfitting
- 📍 Regularization Techniques, Bias-Variance Tradeoff, Model Complexity, Cross-Validation

Module 6 - Machine Learning Algorithms

Linear Regression
- 📍 Assumptions, Ordinary Least Squares, Multicollinearity, Residual Analysis

Logistic Regression
- 📍 Binary Classification, Sigmoid Function, Log-Likelihood, Odds Ratio, Multiclass Classification

Decision Trees
- 📍 Tree Construction, Gini Index, Entropy, Pruning, Decision Tree Limitations

Random Forests
- 📍 Ensemble Learning, Bagging, Feature Importance, Random Forests vs Decision Trees

Xgboost
- 📍 Boosting Techniques, Building Xgboost Models.

Support Vector Machines (SVM)
- 📍 Kernel Trick, Margin Maximization, Soft Margin, SVM for Regression

K-Means Clustering
- 📍 Elbow Method, Cluster Initialization, Distance Metrics, Clustering Evaluation

Hierarchical Clustering
- 📍 Dendrograms, Agglomerative Method, Distance Measures, Cluster Number Determination

Introduction to Neural Networks
- 📍 Activation Functions, Network Architectures, Backpropagation, Loss Functions

Module 7 - Natural Language Processing

NLP Fundamentals
- 📍 Intro to NLP , Machine Understanding Words, Vectorizers , Simple NLP models, Sentiment Classification Project

Module 8 - Industry Projects

SmartGuard: End-to-End Predictive Maintenance for Industrial Automation
- 📍 Task 1: Data Engineering - The Foundation of Predictive Insights
- 📍 Task 2: Exploratory Analysis & Feature Engineering - Uncovering Hidden Signals
- 📍 Task 3: Predictive Modelling - Crafting the Crystal Ball
- 📍 Task 4: Deployment & Monitoring Using Azure - Bringing the Model to Life

Feedback Fusion: Enhancing Business Intelligence through Customer Sentiment Analysis
- 📍 Task 1: Data Collection & Integration - Building the Feedback Repository
- 📍 Task 2: Text Preprocessing & Basic NLP - Preparing the Data
- 📍 Task 3: Sentiment Analysis & Insight Extraction - Understanding Customer Sentiments
- 📍 Task 4: Dashboard Development & Deployment Using Azure - Bringing Insights to Action

Bonus Module - GenAI

Intro to GenAI and OpenAI
- 📍 Understanding GenAI, Connecting with OpenAI , Building Natural Language to SQL using Gen AI

Course Starts:

Live

13-April-2024

Course Duration:

3 Months

Mode of the Course:

Live

Class Timings:

Saturday & Sunday [03:00 PM - 05:00 PM Live Teaching, 05:00 PM to 05:45 PM Live Doubt Session] (IST)

Class Duration:

2 Hours Live Teaching, 45 minutes Doubt Solving

Class Recording Provided:

Yes

Course Validity:

1 year

Programming Language Used:

Python

Prerequisite:

Check Our Complete Python Course

Data Science Bootcamp 1.0 (Live Classes)

LanguageEnglish

Sessions 24

Duration 3 Months

Starts On In Progress

Validity 1 Year

Mode Live

Tech stack you'll learn

Course Content

Course Schedule

Instructor

Shubhankit Sirvaiya

Related Courses

Data Science Bootcamp 1.0 (Live Batch)

Namaste 🙏