COLLABORATION WITH


Data Science : With Python


Enrolled Students:- 150+
Resume Shortlisted:- 40+
Got Hired:- 10+
Life time access for customized Dashboard
Earn program completion and Internship completion certificate


Career Options

  1. Business Intelligence (BI) Developer
  2. Data Architect
  3. Application Architect
  4. Infrastructure Architect
  5. Data Scientist
  6. Data Analyst
  7. Machine Learning Scientist

What will you learn?

  1. Python for Data Science
  2. Introduction to Statistics
  3. Theoretical knowledge and practical aspects of Machine Learning
  4. Basic knowledge of Artificial Intelligence
  5. Neural Networks and working
  6. LSTM and sequence prediction
  7. Data science capstone project

Skills Gained



  1. Proficient use of Python libraries for data exploration and visualization.
  2. Basic understanding and hands-on experience in building machine learning models using Python.
  1. AApplication of statistical concepts for data interpretation and hypothesis testing
  2. Ability to clean and preprocess raw data for effective analysis and modeling.


PROGRAM LESSONS

Chapter 1. Introduction Python
  • 1.1-Python Crash course Introduction
  • 1.2 Python Demo n install
  • 1.3 Python Intro and Installation
  • 1.4 Basic python and datatype
  • 1.5 Basic,Number,string
  • 1.6 Data types
Chapter 2 - Control flow
  • 2.1 If else conditions
  • 2.2 While & for loop conditions
Chapter 3 - Exception Handling
  • 3.1 Exception Handling
Chapter 4 -Functions
Chapter 5 - OOPS
  • 5.1 CLASSES
  • 5.2 OOP
Chapter -6 Deep Learning
  • 6.1 Logistic Regression vs DL
  • 6.2 TesorFlow and Keras
Chapter -7 Libraries
  • 7.1 Introduction to Libraries
  • 7.2 Library Introduction
  • 7.3 Matplolib
  • 7.4 Numpy
  • 7.5 Pandas
Chapter 8 - Mathematics
  • 8.1 Data
  • 8.2 Linear Algebra
  • 8.3 Statistics
  • 8.4 Stats - Probs
Chapter 9. Intro to Probability & DV
  • 9.1 Introduction to Probability, Statistics & SQL
  • 9.2 Data Visualization with Tableau
  • 9.3 LSTM
Chapter 10 - Machine Learning Models
  • 10.1 Clustering
  • 10.2 Evaluation Metrics
  • 10.3 Logistic Regression - Feature Regression
  • 10.4 Logistic Regression
  • 10.5 Simple Linear regression
  • 10.6 Multiple Linear regression
Check Curriculum


PROJECT

Design
ChatBot

ChatBot: AI-powered conversational interface.

Content
Hierarchical Clustering

Hierarchical Clustering: Grouping data hierarchically for analysis.


Design
Surprise Housing Case Study

Surprise Housing: In-depth housing market case study.

Content
Linear Discriminant Analysis

Linear Discriminant Analysis: Data dimension reduction technique.




PRICING PLANS

Standard Plan

Rs. 1999

+18% GST
  • Program Duration : 2 month
  • 2 Major Projects
  • 30+ Hours of content
  • Internship Offer Letter
  • Internship Completion Certificate
  • Program Completion Certficate
  • Fee is applicable only for the platform
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Student Choice

Rs. 2699

+18% GST
  • Program Duration : 3.5 months
  • 25+ Hours of Content
  • 4 Projects
  • Live Sessions During Project Execution & Training
  • Microsoft Certification
  • Internship Offer Letter
  • Internship Completion Certificate
  • Project Report
  • Fee is applicable only for the platform and Microsoft certification examination
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