Machine Learning With Python Training 2019-05-21T13:11:42+05:30

Artificial Intelligence Training

  • 44+ hours of self-paced video
  • 48 hours of instructor-led training
  • Instructor-led online project mentoring sessions

Artificial Intelligence is a way of making a computer, a computer-controlled robot, or a software think intelligently, in the similar manner the intelligent humans think. A computer-controlled robot, or a software think intelligently, in the similar manner the intelligent humans think

Online Training

Rs. 11,999 *90 days access


Self Paced Learning

Rs. 6,999 *180 days access

1 Week Money Back Guarantee
  • 40% Discount
  • Expert Educators
  • Flexible Schedule
  • 24x7 Tech Support
  • GET IN TOUCH

Upcoming Batches

15
Dec

Mon – Fri ( Weekdays )

09:30 AM – 10:30 AM ( IST )

20% Off

16
Dec

Sat – Sun ( Weekends )

7:30 AM – 09:30 AM ( IST )

20% Off

Can’t find convenient schedule? Let us know

Training Features

Instructor-led Sessions

30 hours of Online Live Instructor-led Classes. Weekend class:10 sessions of 3 hours each and Weekday classes.

Real-life Case Studies

Live project based on any of the selected use cases, involving Big Data Analytics.

Assignments

Each class will be followed by practical assignments which can be completed before the next class.

Lifetime Access

You get lifetime access to the LMS, Class recordings and presentations can be viewed online from the LMS.

24 x 7 Expert Support

We have 24×7 support team available to help you with any technical queries you may have during the course.

Forum

Towards the end of the course, you will be working on a project. Big Data and Hadoop Expert based on the project.

Description

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Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry’s standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type specimen book. It has survived not only five centuries, but also the leap into electronic typesetting, remaining essentially unchanged.

Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry’s standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type specimen book. It has survived not only five centuries, but also the leap into electronic typesetting, remaining essentially unchanged.

  • Lorem Ipsum has been the industry’s standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type
  • Lorem Ipsum has been the industry’s standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type
  • Lorem Ipsum has been the industry’s standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type
  • Lorem Ipsum has been the industry’s standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type

Lorem Ipsum has been the industry’s standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make.
Marketing Professionals
Marketing Professionals can enhance their career by learning Digital Marketing. It can help them with their career and make a better decision on their marketing platform.
Graduates
Any graduates can learn this modern marketing technique. It can help them enter an ever-growing field extremely demanded in the modern era of digital technology.
CEOs
CEO professionals can learn Digital Marketing too. They can be confident in making decisions and contributing to the marketing strategy, thus making them more professional.
Business Owners
Business Owners are highly welcomed to learn this course. They can apply this marketing methodology to increase their brand awareness, increase their revenue, and much more.
IT Professionals
IT Professionals have a big deal of benefit in learning this course.
Lorem Ipsum has been the industry’s standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type specimen book. It has survived not only five centurie.

    • According to a source, total internet users in Singapore will increase to 4.93 million SGD in 2022.
    • According to a source, total smartphone users in Singapore will increase to 4.82 million SGD in 2022.
    • The salary package differs from the role applied by a person:
      • The average salary for Digital Marketing Executive is between 30,000 – 38,400 $
      • The average salary for Assistant Digital Marketing Manager is between 38,000 – 54,000 $
      • The average salary for Lead Digital Strategist is between 45,000 -58,000 $
      • The average salary for Digital Marketing Manager is between 55,400 – 90,000 $
      • The average salary for Digital Marketing Director is between 1,30,000 + $
  • Countries paying high to their Digital Marketers are Australia, Netherlands, USA, Canada, UK, Singapore, Spain and more.
  • Companies adopting Digital Marketing increased their profits by 26%.
  • Singapore Companies hiring Digital Marketers are Singapore Airlines, Scoot, Grab, Zendesk, Purple Click Media and many more.

There are no particular pre-requisites for learning this course. You only need to know how to use the system and the internet. You should also understand the methods to the search engines. Well, an excellent language skill is an added advantage.

Artificial Intelligence Course Curriculum

Course 1. Machine Learning with Python

Duration: 45 Hours

  • Introduction of AI
  • History of AI
  • Requirements for AI
  • Use cases & Applications in AI

  • Variables
  • coefficients
  • linear equations
  • graphs of functions
  • histograms
  • logarithms
  • derivatives
  • Matrix multiplication
  • Uses of Algebra in Machine Learning

  • Descriptive statistics
    • Mean
    • median
    • outliers
    • N percentiles
    • variance
    • standard deviation
    • skewness (symmetry)
    • kurtosis (peakness)
  • Inferential statistics
    • Probability concepts
    • Probability distributions
    • Random variables
    • Navies baye’s
    • Central limit theorem
    • Hypothesis testing
      • Z Test
      • T Test
      • F Test
      • ANNOVA (Analysis of Variance)
    • Uses of statistics in Machine Learning

  • Concept of a derivative
  • Gradient or slope
  • Partial derivatives
  • Chain rule (back propagation algorithm for training neural networks)
  • Uses of Calculus in Machine Learning

Proficiency in programming basics in Python

  • Variables
  • assignment
  • basic data types
  • Defining and calling functions
  • positional and keyword parameters
  • Dictionaries
  • lists
  • sets (creating, accessing, and iterating)
  • for loops
  • for loops with multiple iterator variables
  • if/else conditional blocks
  • conditional expressions
  • String formatting/manipulations
  • The pass statements
  • Break/continue statements

  • List comprehensions
  • Lambda functions

  • Matplotlib (for data visualization)
    • pyplot module
    • cm module
    • gridspec module
  • Seaborn (for heatmaps)
    • heatmap function
  • pandas (for data manipulation)
    • DataFrame class
  • NumPy (for low-level math operations)
    • linspace function
    • random function
    • array function
    • arange function
  • scikit-learn (for evaluation metrics)
    • machine learning basic models
    • metrics module

  • Machine Learning Introduction
  • Types of Machine Learning
  • Supervised Machine Learning
  • Un Supervised Machine Learning
  • Reinforcement Learning
  • Neural networks overview
  • Deep Learning overview

  • Data Extraction
  • Data Cleansing & Transformations
  • Data Preparations
  • Model Selection
  • Train the Model
  • Test the Model
  • Validate the Model
  • Measure the accuracy of the model
  • Deploy the model
  • Tune/Rebuild the model

Supervised Machine Learning Algorithms

  • Regression models
    • Linear Regression
    • Non Linear Regression
    • Lasso Regression
    • Ridge Regression
    • Gradient descent algorithm
  • Classification models
    • Logistic Regression
    • Naïve Bayes Classification
    • Decision Tree
    • Random forest
    • SVM Classifier (support Vector machines)
    • GBM (gradient boosting)

  • Clustering Models:
    • K-Means
    • Hierarchical Clustering
  • Neural Networks:
    • Introduction to Neural Networks
    • Training Neural Networks: Best Practices
    • Multi-Class Neural Networks
  • Deep Learning:
    • Introduction to Deep Learning
    • Deep Learning Models
    • Deep Learning Platforms and Software Libraries

  • Introduction to TensorFlow
  • Installing TensorFlow
  • TensorFlow features
    • Tensors – TPU
    • Estimator (tf.estimator)
    • tf.layers/tf.losses/tf.metrics
    • Lower-level TensorFlow
  • TensorFlow Usecases

  • Keep your first model simple.
  • Focus on ensuring data pipeline correctness.
  • Use a simple, observable metric for training & evaluation.
  • Own and monitor your input features.
  • Treat your model configuration as code: review it, check it in.
  • Write down the results of all experiments, especially “failures.”

  • Will provide the below ML Use cases with real time datasets along with train, test and validation of the model.

  • Iris dataset process
  • Titanic dataset

  • Loan Prediction Data
  • Sales Prediction
  • Customer Understanding

Course 2. Bigdata /Hadoop

  • BigData Concepts
  • 3V’s (Volume, Verity, Velocity)
  • Challenges & Solutions of BigData
  • Use Cases of BigdData

  • Hadoop Architecture
  • Hadoop History
  • Hadoop Features
  • HDFS
  • MapReduce Architecture
  • MapReduce Process flow
  • Sqoop
  • Hive

  • Spark Architecture
  • Spark Vs Map Reduce Processing
  • Spark Process Engine advantages
  • Spark core concepts
  • RDD
    • RDD operations
    • DAG mechanism
    • Transformation in RDD
    • Actions
  • Data Frames & Data Sets
  • Working with PySpark
  • Spark SQL
  • Spark ML Library

  • Kafka Architecture
  • Use cases of Kafka
  • Configuring Kafka Cluster
  • Kafka topics
  • Producer/Publisher
  • Consumer/Subscriber
  • Kafka Brokers/Servers
  • Working with Kafka Flow

  • Introduction of NoSQL
  • What is SQL
  • What is NOSQL
  • Brewer’s CAP Theorem
  • Introducing Cassandra
  • Distributed and Decentralized
  • Cassandra Architecture
    • Ring distributed architecture
    • Peer-to-Peer
    • Gossip protocol
    • Failure Detection
  • Elastic Scalability
  • High Availability and Fault Tolerance
  • Tunable Consistency
  • Column-Oriented
  • High Performance

  • Installation of DataStax Cassandra
  • Installation of Dev Center

  • CQL – Cassandra Query Language
  • Keyspaces
  • CQL Tables
  • Partition Keys / Primary Key
  • Cluster Keys
  • Composite Keys
  • Secondary Indexes
  • Materialized Views

  • Eventual Consistency
  • CQL Batch
  • Eventual Consistency & Tunable Consistency
  • Alter & Drop Table
  • Commit Log
  • Mem Table
  • SS Table
  • How writes works
  • How reads works
  • Scalability
  • Partitioning
  • Replication
  • Compactio

  • Introduction of Airflow
  • Configuration
  • Realtime Use cases

Course 3. GCP (Google Cloud Platform)

  • Introducing Google Cloud Platform
  • Advantages of Google Cloud Platform.
  • Define the components of Google’s network infrastructure, including:
    • Points of presence
    • data centers, regions, and zones
  • Understand the difference Cloud Services
    • Infrastructure-as-a- Service (IaaS)
    • Platform-as-a-Service (PaaS).
    • Software-as-a-Service (SaaS).
    • Machine Learning-as-a-Service (MLaaS).
  • GCP Registration
  • Walk through GCP Dash board
  • API & Services
  • IAM & Admin
  • COMPUTE
    • App Engine
    • Compute Engine
    • Kubernetes Engine
  • STOREAGE
    • Cloud Storage
    • SQL Storage
    • NoSQL Storage
    • Spanner
  • Cloud BigData/Machine Learning
    • BigQuery
    • Pub/Sub
    • DataProc (Hadoop cluster)
    • DataFlow
    • Machine Learning Engine
    • DataPrep

Note : Use Cases will be explained by Using all above technologies (BigData, NoSQL, Cloud and Machine Learning)

Certification

Quality Thought’s Artificial Intelligence Certification Process:

  • Quality Thought will provide a certificate to the students who successfully completed their Artificial Intelligence training. The certification will be provided within one week of the training completion.
  • The certification will be given to the students who have successfully completed their projects and assignments on time.

Frequently asked questions

Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry’s standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type specimen book. It has survived not only five centuries.
Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry’s standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type specimen book. It has survived not only five centuries.
Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry’s standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type specimen book. It has survived not only five centuries.

  • Classroom Training
  • Online Training
  • Corporate Training
  • Self-paced Training

The group containing 3 and more members, will have 20% discount for each member.

Artificial Intelligence Training Reviews

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Karthik

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Sruthi

Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry’s standard dummy text ever since the 1500s.
Ramesh

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