Data Science With Generative AI
TRAINING & PLACEMENT PROGRAM
The course "Data Science with Python, Stats, Machine Learning, Deep Learning, and Generative AI" is tailored for intermediate learners. This all-encompassing program delves into crucial areas such as Python for data science, statistics, machine learning, deep learning, and generative AI. Participants will acquire practical skills in data analysis, constructing machine learning models, and implementing deep learning techniques with Python. By the course's conclusion, learners will have a robust grasp of these subjects, equipping them for advanced studies and career advancement.
Enroll Now
9500+
Students Enrolled
Learning Mode
Online & Offline
Duration
8 Months
Internship
6 Months
Certification
By Slidescope
Start Date
18 AUgust
- About Course
The "Data Science with Python, Stats, Machine Learning, Deep Learning, and Generative AI" course offers a comprehensive learning experience for intermediate learners seeking to deepen their knowledge in data science. This extensive program covers key topics including Python programming, statistical analysis, machine learning algorithms, deep learning techniques, and generative AI models. Students will engage in hands-on projects to gain practical experience in data manipulation, model building, and deploying advanced AI applications. By the end of the course, participants will have developed a strong foundation in these essential areas, empowering them for advanced academic pursuits and professional growth in the field of data science.
- Important Highlights
- 200+ Hours Live Sessions
- Personalized Career Mentorship
- Monthly Mock Interviews
- Personalized Training
- Internships for Live Training
- 50+ Hours Doubt Sessions
- Resolution of Doubts
- Live Industry Session
- 1 Year LMS Access
- 30 Industry Projects
- Course Curriculum
- 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
Do yo need free career counseling
We will be happy to help you
Sample Certificate
- Our Students
- Our Faculty
Er. Amit Tyagi
Amit Ji has a combined experience of 18+ 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.
Founder - Kanity Solutions
