Data Science With Generative AI

Training & Placement Program

The “Data Science with Python, Stats, Machine Learning, Deep Learning, and Generative AI” course is designed for intermediate learners. This comprehensive program covers essential topics including Python for data science, statistics, machine learning, deep learning, and generative AI. Participants will gain practical skills in data analysis, building machine learning models, and applying deep learning techniques with Python. By the end of the course, learners will have a solid understanding of these areas, preparing them for advanced studies and career progression.

Watch Intro

Go thru the intro video to understand more

Mode

Offline & Online

9600+

Students Enrolled

Certificates

By Slidescope

3 Months

Internship

5

Practice Interviews

  • Installation and Introduction to Excel
  • Understanding the Structure of the Workbook & Worksheet Excel Calculation
  • Excel File Handling
  • Excel Formulas and Functions
  • Excel Advance - VLOOKUP, Pivot Chart, Basic Macros, and More Data Analysis
  • Hands-on Sessions and Assignments for Practice
  • Excel – Non-Graded Exam
  • Installation and Introduction to MySQL
  • MySQL Databases
  • Table and Views
  • Statements and Fundamentals
  • Data Types in MySQL
  • Aggregate Functions
  • SQL Constraints
  • SQL Joins
  • Union and Union All
  • Clauses in MySQL
  • Control Flow Function
  • Conditions in MySQL
  • Hands-on Sessions and Assignments for Practice
  • MySQL – Graded Exam
  • Basics of Power BI
  • Types of Graphs and When to create them
  • Working with Filters
  • Calculated Columns, Calculated Measures & Calculated Tables
  • Formatting and Styling of Graphs and Dashboards
  • Writing basic and Advanced DAX Queries
  • Data Visualization using Power BI
  • Hands-on Sessions and Assignments for Practice
  • Power BI – Graded Exam
  • Basics of Google Looker Studio
  • Getting Started
  • Connecting Google Sheets, CSV, Excel files
  • Connecting Google Analytics, Google Search Console Files
  • Digital Marketing Data Analytics with Looker Studio
  • Creating Graphs, Dashboards, Pages, and Reports with Looker Studio
  • Basics of Tableau and its different versions
  • Software Installation and Online Authoring
  • Connecting CSV, Excel, JSON, MySQL, Postgresql, MSSQL etc. with Tableau
  • Digital Marketing Data Analytics with Tableau
  • Creating Graphs, Dashboards, Stories, and Reports with Tableau
  • Calculated Fields, Parameters, Groups in Tableau
  • Filters at different Level in Tableau
  • Relationships and Joins in Tableau
  • Clustering, Trend Analysis and Forecasting Data With Tableau
  • Exercise on different projects in Tableau
  • Introduction and Software Installation
  • Basic of Python
  • Data Types and Operations with different types of data
  • Control Statement and Looping
  • Data Structures
  • Functions in Python
  • Libraries
  • File Handling
  • Exception Handling
  • Hands-on Sessions and Assignments for Practice
  • Python – Graded Exam
  • Working with JSON Data and JSON APIs
  • Learn Python Pandas in detail
    • Series and Dataframe Basics
    • Connecting with Excel, Csv, Json, SQL and HTML datasets
    • Data Cleaning, Missing Data Handling
    • Exporting to Excel and CSV files
    • Reshaping: Crosstab, Melt, Pivot, Join, Merge, Groupby etc.
    • Plotting Bar, Pie, Line, Scatter, Box, Histogram etc. graphs with Pandas
    • Working with TimeSeries Data & its analysis
  • Learn Seaborn & Matplotlib for Advanced Data Visualization
  • Supervised and Unsupervised Machine Learning concepts
  • Applying Linear Regression, Logistic Regression algorithms on datasets
  • Applying Decision Tree, Support Vector Machine, Random Forest etc. Classification algorithms on datasets
  • Working with Clustering and other Unsupervised Algorithms
  • Creating Machine Learning Models
  • Introduction and Implementation
  • Lexical Processing
  • Syntactic Processing
  • Semantic Processing
  • Introduction to Neural Networks
  • Hands-on Sessions and Assignments for Practice
  • NLP – Graded Exam
  • Introduction to Deep Learning
  • Introduction to Neural Networks
  • Convolutional Neural Networks
  • Regional CNN
  • Generative Adversarial Network (GAN)
  • Boltzmann Machine & Autoencoder
  • Introduction RNN and GRU
  • Emotion and Gender Detection
  • Auto Image Captioning Using CNN LSTM
  • Hands-on Sessions and Assignments for Practice
  • Deep Learning – Non-Graded Exam

Content for Resume Building and Personality Development

Ankit Srivastava

Ankit has 12+ Years of Experience in Digital Marketing, Software Development and Data Analytics. He has 8800+ Students on Udemy and has taught 300+ students in Classroom Training for last 8 years. He provides Web Development and Digital Marketing consulting to E-Commerce clients .

Amit Tyagi
Amit Tyagi

Amit Ji has a combined experience of 16+ Years in Software Development, Web Development and Digital Marketing.He owns Kanity Solutions and has served more than 100 clients with his IT Consulting. He will share his experience with students of Digital Marketing.

Rachit Srivastava

Rachit has 10+ Years of Experience of handling Sales & Marketing projects of MNCs and State Government. He has MBA from Lucknow University. He teaches concepts of marketing and business intelligence to students.


Our Students Work in these Amazing Companies

tcs
wipro
hcl
axtria
fractal

Our Brilliant Students

Mrinal Prem

Sernior Associate

Axtria

Apoorv Srivastava

Senior Analyzt

Zigram

Aditya Khare

Associate Software Engineer

Tech Mahindra

Mohsin Khan

Sr Executive

Group M

Anmol Jacob

Data Manager

KGMU