IIT Guwahati - Certification in Full Stack Data Science and AI

Offered byAlmaBetter
Private Institute

Certification in Full Stack Data Science and AI
at
AlmaBetter
Overview

Gain expertise in transforming raw data into a format suitable for analysis, including handling missing values, outliers and data normalization

Duration	6 months
Total fee	₹60,000
Mode of learning	Online
Official Website	Go to Website
Credential	Certificate

Certification in Full Stack Data Science and AI
at
AlmaBetter
Highlights

Earn a certificate from IIT Guwahati
Fee payment can be done in instalment
Get placement support
Resume building & mock interviews
2-day campus immersion program at IIT Guwahati

Certification in Full Stack Data Science and AI
at
AlmaBetter
Course details

Skills you will learn

GIT Python MySQL

Who should do this course?

Individuals looking to transition into a Data Science career
Individuals interested in upskilling with an Advanced IIT certification

What are the course deliverables?

Understand the key concepts in data science, AI and machine learning, including data processing, statistical analysis and predictive modeling

Master the mathematical and statistical principles that underpin data science, such as linear algebra, calculus, probability and statistics

Learn methods for collecting, cleaning and preprocessing data from various sources, including structured, unstructured and semi-structured data

Develop skills in visualizing data using tools like Matplotlib, Seaborn and Plotly to identify trends, patterns and insights

Learn to build and train deep learning models using frameworks like TensorFlow and PyTorch

More about this course

Certification in Full Stack Data Science and AI equips professionals with comprehensive skills across the entire data science and artificial intelligence (AI) pipeline

The certification emphasizes practical, hands-on experience, allowing learners to develop and deploy full-stack AI applications that can analyze complex datasets, generate insights and drive decision-making in real-world scenarios

In addition to technical expertise, the program often includes training in data ethics, project management and communication, ensuring that graduates are well-rounded professionals capable of leading data science initiatives across diverse industries

Program Induction: August 21, 2024, at 08:00 PM
Regular Classes: August 21, 2024 - February 21, 2025, from 08:00 PM to 10:30 PM

Premium Icon: 30,000 + 18% GST

Certification in Full Stack Data Science and AI
at
AlmaBetter
Curriculum

Introduction to Computer Programming

Getting Started with Python
Data Types in Python
Indexing & Slicing
In-built Functions and Methods
Conditional Statements
Loops & Iterations
Conditional & Infinite Looping
Advanced Looping Concepts
Custom functions in Python
Lambda & Map Functions
Errors and Exception Handling
OOPs in Python
Coding Best Practices
Arrays and Strings
Recursion - I and II
Sorting Algorithms
Search Algorithms
Competitive Coding

Numerical Programming in Python

Packages & Libraries - OS
Datetime, Regex & Beautiful Soup
Command Line & File System
Git and Github
Standard Data Management Libraries
Data Wrangling using Pandas and Numpy
Data Visualisation Libraries - Matplotlib & Seaborn
Exploratory Data Analysis

Relational Databases

Getting Started with SQL
SQL Environment & Basic Commands
Fundamentals of SQL Query
Dealing with Multiple Tables
Advanced SQL Joins
Mathematical & Data type conversion Functions
DateTime & String Functions
Window Functions
Miscellaneous Functions
Connect & Analyse Data with SQL & Python
Database Management & Schema Design
Competitive Coding & Query Optimisation
Complex queries using CTE & Pivoting
Type Casting & Math Functions
Advanced SQL Joins
Type Casting & Math Functions

Data Visualization Tools

Fundamentals of Excel
Data Exploration with In-Built Functions
Storytelling with Excel
Advanced Dashboarding Concepts - Macros & VBA
Getting Started with Tableau Ecosystem
Choosing the Right Chart - Visual Intuition
Storytelling with Tableau
Intro to Power BI
Intro to Google Analytics
Dashboarding and SQL

Applied Statistics

Calculus for ML
Vector Algebra
Matrix Algebra
Probability Theory
Data Summarization
Probability Distributions - Discrete and Continuous
Joint Distribution
Sampling and Statistical Inference
Concept of Confidence
Hypothesis Testing
Statistical Inference in Industry - A/B testing

Introduction to Machine Learning

Getting Started With ML
ML Lifecycle
Implementing simple Supervised Algorithm
Linear & Tree based models
Implementing simple Unsupervised Algorithm
Unsupervised Clustering: K-means & Hierarchical
Data Preparation for ML Models
Cross validation
Hyperparameter tuning
TedX Views Prediction - Case Study
Customer Segmentation - Case Study
Time Series Analysis
Bagging & Boosting: Complex Algorithms
Nonlinear Algorithms - Polynomial Regression
SVM & Neural Networks
Natural Language Processing
Image processing
Recommender Systems
SQL Feature Engineering, Prediction and Analysis