Grow Data SKills | Most Affordable Courses | Become Top Data Professional

Light
Dark

Complete Data Science - Basic To Advance

By Shubhankit In Grow Data Skills

Self Paced
English
Completion Certificate

Demo Class Video

1 Year

Validity (From the date of Enrollment)

65 Hours

Duration

30

Sessions

2

Projects

INR 5400

Buy Now

This course includes

Content Duration65 Hours
Total Video Sessions30
Total Industry Projects2
Azure Cloud
Quality Assignments & quizzes after each module
Interview preparation guide
Dedicated placement assistance
Resume & Linkedin profile making
Doubt support on private discord community
Certificate of completion

Tech stack you'll learn

Course Content

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

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

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

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

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

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

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

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

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

Attention Seeking Resume Preparation and Interview Strategies
Strategies To Crack Tech Interviews
Linkedin Profile Making
How To Expand Your Professional Network On Linkedin
How To Use Various Job Portals
How To Approach For Referrals

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

Course Schedule

Mode of the Course:

Recorded

Course Duration:

65 Hours

Total Sessions:

Total Projects:

Validity:

1 Year (From the date of enrollment)

Programming Language Used:

Python

Prerequisite:

Check Our Complete Python Course

⚠️ Important Notice :

The video may not work on Linux due to DRM restrictions. It is only accessible on Chrome when using Windows or macOS.

Workaround: To access the video on Linux, you can create a Windows virtual machine (VM) and watch the video through the VM. Alternatively, you can use our Android or iOS application to view the video on your mobile device.

Instructor

Shubhankit Sirvaiya

Shubhankit Sirvaiya is a Data Scientist At World Wide Technology | Ex- Accenture Growth & Strategy , mentored over 700+ students around Data Science Domain.