DATA SCIENCE WITH Python, ML and AI
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DATA SCIENCE WITH Python, ML and AI

 
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The 12 months Python for Data Science course at the Onward Academy introduces the basic concepts of Python and Data Science with Machine Learning and Artificial Intelligence.  This is highly technical course is project-based at its core and will present you with many practical examples before giving you the opportunity to create and run your own Python with ML and AI projects. Learn to leverage data using Python in creative and relevant ways to solve real-world problems. Today Data Science skilled engineers are getting salary of 15L to 28L recruited by Google, Amazon, Uber, IBM and top MNCs. Data analysis helps you in making informed decisions with data exploration and visualization using advanced tools. The Data Science with Python will make you expert in

  • Python Programming
  • Advanced Python
  • Data Science with ML and AI
  • RDBMS with SQL
  • Data Analyst with Tableau

Program Outline : Data Science with Python, ML and AI

Duration : 12 months (Fast Track : 6 months)

Course Outline

Introduction to Data Science

  • Selecting rows/observations
  • Rounding Number
  • Selecting columns
  • Merging Data
  • Data Aggregation

Python overview

  • Python Basics
  • Python Installation
  • Python IDEs

Python Core

  • Data types
  • Lists, Array
  • If, Loops
  • Tuples

Python Functions

  • Date
  • String
  • Mathematicals

Python Packages

  • Pandas
  • Numpy
  • Sci-Kit Learn
  • Mat plot

Python Import data

  • Read Save CSV
  • Loading data objects
  • Writing data

RDBMS with SQL

  • RDBMS and SQL
  • Create table, Select
  • Insert,  update and delete rows
  • Query and Sub Query
  • JOINING and Types
  • SQL functions
  • SQL Nested query and Advanced

Advanced Python

  • Python with Django
  • Python framework
  • Insert, select, update
  • Creating Web app

Manipulating Data

  • Rounding, Selecting
  • Merging data
  • Data Aggregation

Statistics Overview

  • Mean, Median
  • Mode
  • Skewness

Probability and Deviation

  • Types of Probability
  • ODDS Ratio
  • Data Deviation
  • Variance

Error Metrics

  • Classification
  • Regression
  • MSE, RMSE, MAPE

Machine Learning

  • Linear Regresion
  • Logistic regression
  • ROC Curve

SVM

  • Vectors and Hyperplanes
  • 2 D Case
  • Linear and Radial – Kernel
  • Polynomial

ML Algorithms

  • K Nearest Neighbour
  • Decision Tree
  • Random Forest

Artificial Intelligence

  • Perception
  • Multi Layer
  • Markov Decision
  • Logical Agent

Deep Learning

  • CNN
  • RNN
  • ANN

NLP and Processing

  • Text Pre Processing
  • Noice removal
  • Stemming
  • Enitity Parsing

Task of NLP

  • Text Classification
  • Text Matching
  • Phonetic Matching
  • String Matching

Tableau

  • Overview of Tableau
  • Connecting Spreadsheet
  • Connecting SQL
  • Joining Tables
  • Data Blending

Tableau and Reports

  • Arameters
  • Grouping and set
  • Data Labels
  • Reports and Analysis
  • Sort, Filter, Subtotals

Tableau Charts

  • Types of charts
  • Area, Bar chart
  • Bubble chart
  • Other charts

Tableau Advanced reports

  • Dual Axis Reports
  • Blended Axis
  • Reference Distributions
  • Map and Use of Google Map

Tableau Filters

  • Calculated Fields
  • Calculate Ranks
  • Filter types
  • Conditional Filters

Tableau Dashboard

  • Create
  • Format
  • Filters on Dashboard
  • Create Story

Live projects

  • Python and SQL
  • Python and Data Science
  • Tableau Dashboard

JOB PROFILE FOR DATA SCIENCE WITH PYTHON

  • Software Developer
  • GIS Analyst
  • Junior Python Developer
  • Machine Learning Engineer
  • Data Scientist
  • Data Analytics with Python
  • AI Developer
  • Tableau Analysts Programmer

Which companies use Python with AI and ML?

Many of the biggest and most popular companies use Python. Some of them are:

  • Google, NASA, Amazon, IBM
  • Social networking sites like Instagram, Reddit, Quora, etc
  • Media streaming companies like Netflix and Spotify
  • Rideshare companies like Uber and Rapido.

Placement Profile

Duration

  • 1 year (Regular Course) 6 months (Fast Track Course)
  • Regular Classes (Monday to Friday) and Weekend Classes (Saturday and Sunday)

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