Artificial Intelligence Career Essentials
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Artificial Intelligence Career Essentials

The New Bundle Course

Artificial Intelligence Career Essentials

The New Bundle Course!

Our comprehensive career bundle is the power of Data Science, Machine Learning, Data Analytics, Data Visualization & Python programming.  This fuels you to implement AI concepts into creating real world applications. 

Language: English

Buy Course Bundle worth ₹14692 @

Price: ₹2999 only

Our comprehensive career bundle is the power of Data Science, Machine Learning, Data Analytics, Data Visualization & Python programming.  This fuels you to implement AI concepts into creating real world applications. 

  Language: English

Buy Course Bundle worth ₹14692 @

Price: ₹2999 only

*Limited time offer

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About this Course Bundle

About this Course Bundle

Our comprehensive course bundle is the power of Data Science, Machine Learning, Data Analytics, Data Visualization & Python programming.  This fuels you to implement AI concepts into creating real world applications. You’ll also be able to solve business problems with the blend of AI solutions learnt through our course.

100% online and Self-paced learning

Full lifetime access

Dedicated Forum Support 

Courses you get in this Bundle:
Data Analytics using Pandas 

3 Modules

Keras for Beginners

3 Modules

Data Engineering and Big Data

3 Modules

Machine Learning

1 Module

Data Visualization using Python

3 Modules

R Programming

3 Modules

Data Science with R

2 Modules

Ethical Hacking

1 Module

Unlike other courses, GUVI believes in hands-on project learning & frequent assessment for every course, so you will learn to program by building & hosting real-time applications on cloud.

*Limited time offer

*Limited time offer

What will you achieve?
  • How to build Classification & Regression Models.
  • Learn to run ML models.
  • Understand the core concepts of Data Science
  • Implement Deep learning in a meaningful way
  • Understand the concepts of Databases & Data Warehouse
  • Handle Big Data & Parallel computing
  • Implement Deep learning in a meaningful way
  • Understand the concepts of Databases & Data Warehouse
  • Handle Big Data & Parallel computing

*Limited time offer

*Limited time offer

Prerequisites

Prerequisites

  • Basic Coding knowledge
  • Curiosity to learn new technologies
Who is the course for?

Who is the course for?

  • Excellent opportunity for those looking to advance their careers in Artificial Intelligence. 
  • Data science/Data visualization/Data Analysis Enthusiasts.
  • Students, Early professionals or anyone who wants to switch themselves to a Data Science / AI career.

The average salary for a Artificial Intelligence Engineer is ₹2,000K / yr in India.

What you will learn from this course bundle ?
Data Analytics using Pandas Syllabus:
Beginner Module

Introduction
Setting up Pandas Environment
An Introduction to Jupyter Notebook
Loading Data into Pandas
A Deeper Look Into Data
DataFrames - Basic Functions
dataframes- rows and columns

Intermediate Module

Sorting DataFrames
Handling Datetime Fields in Pandas
Statistical Functions in Pandas

Advanced Module

Pandas - Indexes
Data Grouped Representation
Data Visualization
Adding New Data - Merge, Join
Adding New Data - Append/Concat
Final Project & End Note

Keras for Beginners Syllabus:
Beginner Module
  • Welcome to Keras for Beginners course
  • Course Walk Through
  • Getting Started with Colab 1 - First Taste of Colab
  • Getting started with Colab 2 - More about Colab
  • Getting Started with Colab 3 - Little beyond the basics of Colab
  • Introduction to Keras 1
  • Introduction to Keras 2
  • Introduction to Keras 3
  • Introduction to Keras 4
  • Introduction to Keras 5
Intermediate Module
  • Fully Connected Networks - 0 - Project Overview
  • Fully Connected Network - 1 - Preprocessing the Data
  • Fully Connected Network - 2 - Creating the Model
  • Fully Connected Network - 3 - Training the model
  • Fully Connected Network - 4 - Saving the Model
  • Fully Connected Network - 5 - Testing and Evalution
  • Fully Connected Network - 6 - Improving the Model Performance
  • OPTIONAL SUGGESTED STUDENT PROJECT 1 - Fully Connected Network
  • Convolutional Neural Networks - 0 - Project Overview
  • APPENDIX 1 - Basics of Convolutional Neural Networks
  • Convolutional Neural Network - 1 - Data Preprocessing
  • Convolutional Neural Network - 2A - Building the Model - Conv Layers
  • Convolutional Neural Network - 2B - Building the Model - Dense Layers
  • Convolutional Neural Network - 3A - Training the model
  • Convolutional Neural Network - 3B - Improving the Network Performance
  • Convolutional Neural Network - 3C - Improving the Network Performance
  • NLP - 0 - Project Overview
  • NLP - 1A - Text Data Processing - Built-in Dataset
  • NLP - 1B - Raw Data Processing
  • NLP - 1C - Raw Data Splitting
  • NLP - 2A - Tokenize Text Data
  • NLP - 2B - Padding
  • NLP - 3A - GloVe Word Embeddings
  • NLP - 3B - Embeddings Matrix
  • NLP - 4 - Fully Connected Network for Text Analysis
  • NLP - 5 - CNNs for Text data
  • NLP - 6 - RNNs for Text Data
  • NLP - 7 - LSTMs for Text Data
  • OPTIONAL STUDENT PROJECT EXERCISES NLP
Advanced Module
  • Transfer Learning - 0 - Project Overview
  • Transfer Learning - 1 - Project Overview - Introduction to Transfer Learning
  • Transter Learning - 2 - Project Overview - Introduction to Kaggle Datasets
  • Transfer Learning - 3A - Importing Kaggle Dataset
  • Transfer Learning - 3B - Data Preprocessing
  • Transfer Learning - 4 - Base Model
  • Transfer Learning - 5 - Keras Functional API
  • Transfer Learning - 6 - Classification Layers
  • Transfer Learning - 7 - Training with fit_generator
  • Course Wrapup - Beyond The Basics
Data Engineering & Big Data Syllabus:
Beginner Module

Introduction to Course
Python Introduction and Installation
Basic Syntax of Python
Data Structures in Python
Python Built-in Functions
User Defined Functions in Python
Modules and Packages in Python
Introduction to Databases and MySQL Installation
SQL-1
SQL-2
SQL-3
SQL-4
SQL Assignment

Intermediate Module

Python Assignment
Data Warehousing Concepts
OLAP and its Operations
Bigdata and Parallel Computing
Hadoop and its Ecosystem
HDFS Architecture and File Storage
HDFS Installation and Commands
HDFS Assignment
Map Reduce and word count example
Map Reduce Workflow
Data Storage File Formats
YARN
Map Reduce Assignment

Advanced Module

Introduction to Apache Spark
Spark Architecture and Toolkit
Spark APIs : RDD
Transformations and Actions
Spark APIs: Distributed Shared Variables
Spark APIs : Dataframes and Datasets
Spark APIs : Spark SQL
Spark Execution Modes
Spark Application Life cycle and Tuning
Spark Hands on Examples-1
Spark Hands on Examples-2
Spark Dataframe, RDD, Spark SQL Assignment

Machine Learning Syllabus:
Machine Learning

About Machine Learning Course
Installation of Anaconda
What is Machine Learning
Types of Machine Learning, Supervised Learning and Regression
Types of ML,Logistic Regression and Unsupervised Learning
SVM -What is SVM and How do they work
SVM-Loading and Examining our dataset
SVM-Building and Tweaking our SVM Classification mode
What is Decision Tree?
Building the Decision Tree : Decision Tree Learning
Building a Decision Tree - Information Gain a Gini Impurity
Decision Tree Lab:Building our First Decision Tree
Decision Tree Lab:Viewing and Tweaking our Decision Tree
What is Overfitting
Random Forest Lab
Teamwork
Avoiding Overfitted Models

Data Visualization using Python Syllabus:
Beginner Module
  • Introduction to Data Visualization
  • Matplotlib for Data Visualization
  • Using Matplotlib to draw plots
  • Visualizing & Customizing Plot appearances using Matplotlib
  • Multiple Line PLots
  • Basics of Time Series Plotting
  • Time Series Plotting and adding styles to the plots
  • Slicing and Customizing Time Series Data
  • Twin Axes Plotting
  • Bar Plot and Box Plots
  • Violin, Histogram and Scatter
  • Contour Plot and Annotations in Matplotlib
  • Advance Annotations
  • Image Tutorial in matplotlib
Intermediate Module
  • Introduction to Seaborn Library
  • Relational Plots and Subplots in Seaborn
  • Subplotting in Rows and Columns using Relational Plot
  • Line Plots in Seaborn
  • Bar Plots, Box Plots and Point Plots in Seaborn
  • Colour Palettes in Seaborn
Advanced Module
  • Introduction to BOKEH
  • Patch Plots and Scatter Marks in Bokeh
  • Area Plots and Circle Glyphs in Bokeh
  • Rectangle, Oval and Polygon Glyphs in Bokeh
  • Wedges, Arcs and Specialized curves in Bokeh
  • Setting Plot ranges and Axes in Bokeh Plots
  • Twin Axes, Datetime axes and Annotations in Bokeh Plots
  • Categorical and Log Axes in Bokeh
  • Row and Column Layouts in Bokeh Plots
  • Customizing Tools and Legends in Bokeh Plots
  • Column Data Source and Adding Widgets to Bokeh Plots
R Programming Syllabus:
Beginner Module
  • R - An Introduction
  • Variables and Operators
  • Vectors
  • Matrices
  • Lists
  • Data Frames
  • Factors and Datasets
  • Summarise functions
  • Conclusion
Intermediate Module
  • Relational Operations
  • Logical Operations
  • Control Statements
  • Looping Statements and Functions
  • Mathematical and Statistical Relational Functions
  • apply functions
  • map functions
Advanced Module
  • Dplyr Select
  • Dplyr - Slice, Mutate, Arrange
  • data.table - Select, Filter and Sort
  • Joins
  • Grammar of Graphics
  • Plots and Histograms
  • Pie Charts
  • ggplots
  • Project Task
  • Project Task Solution
Data Science with R Syllabus:
Beginner Module

Basics of Data science
Assignment 1
Introduction to Big data
Application of Big data Analytics
Introduction to R
In-Built functions in R
Basics of Statistics
Hypothesis testing
Statistical tests
Some more inbuilt functions in R
Statistical operations in R
Plotting in R
Basics of Machine learning
simple linear regression theory
Simple linear regression in R
Multiple linear regression theory
Multiple linear regression in R

Intermediate Module

Logistic regression
Metrics in logistic regression
Logistic regression model in R
Logistic regression metrics in R
Decision tree
CHAID
Random Forest
Random forest in R
Introduction to Clustering
Introduction to K-Means clustering
K-Means in R

*Limited time offer

*Limited time offer

Our Learners
Midhun Devasia

You will be lucky to find quality courses on GUVI. I must say that I was really lucky to get courses at such a low and discounted price. I got more than 9 hours of video and around 20 more resources to gain knowledge of programming. GUVI provides a wide variety of courses both technical and non-technical. I suggest GUVI is the best choice.

Arjun Govindan

What makes GUVI different is that it provides vernacular courses which make it easy to understand & practice platforms like CodeKata, WebKata & MicroArc, all these helped me improve my practical programming skills in the front end, back end. I highly recommend it if you want to get started with something new.

Pranav Mahadeokar

I have opted for a combo-course that starts with the basics of the popular technologies and made me a pro in its domain... Codekata is very damn helpful to crack placements because it improved my efficiency in coding... we just need to be persistent and that’s all it takes. I am very happy to encounter GUVI!

*Limited time offer

Get Unlimited Access to Our Practise Platform

CodeKata

A tool-kit specifically developed to boost the coding skills and makes you ever-ready to crack interviews.

WebKata

A cloud-based module to hone your front end skills without any hassle of local environment setup.

MicroARC

MicroARC is a standardized skill assessment platform powered by Artificial Intelligence with a huge question library. 

Verified Certificate

 Verified Certificate

You can share your Course Certificates in the Certifications section of your LinkedIn profile, on printed resumes, CVs, or other documents.

  • Certificates are issued by an IIT-M incubated company-GUVI.
  • Certificates are globally recognized & they upgrade your programming profile.
  • Certificates are generated after the completion of course.
  • Certificates are sharable on your LinkedIn profile.

*Limited time offer

*Limited time offer

You can share your Course Certificates in the Certifications section of your LinkedIn profile, on printed resumes, CVs, or other documents.

Frequently Asked Question

What is the refund policy?

Customer satisfaction is our first priority. If you are not satisfied with the course, send a mail to [email protected] with the reason for refund and your feedback on the course with the subject line "ProductThinking – Refund” , within 7 days of purchasing the course. Your refund will be processed immediately. 

Will I gain access to any sort of Forum support?

Yes. You will gain complete access to our forum support to connect with our fellow aspiring users. 

Apart from these courses, will I get access to any practice platforms?

You will gain access to CodeKata which is a gamified practice platform which hosts 1000+ curated coding problems and MicroARC, which is an interactive skill assessment platform which helps you to test your skills. 

On what basis are the certificates rolled out?

The certificates are rolled out as and when you complete a course. 

Is it 100% online learning or should I come in person for any specific course?

It is a 100% online learning course package and there won’t be any necessity for you to be present in person. 

Artificial Intelligence Career Essentials 

The New Bundle Course

The New Add-on Course to PRO

Our comprehensive career bundle is the power of Data Science, Machine Learning, Data Analytics, Data Visualization & Python programming.  This fuels you to implement AI concepts into creating real world applications. 

Language: English

Buy Course Bundle worth ₹14692 @

Buy Course Bundle worth ₹14692 @

Price: ₹2999 Only

Price: ₹2999 only

*Limited time offer

Please wait