Machine Learning Course Fee in Kochi

Classroom

  • 8-Day(4 weekends) Intensive Program
  • 3 Months Live Project Mentoring
88000
44000

Live Virtual

  • 80 Hrs Live Virtual Intensive Program
  • 3 Months Live Project Mentoring
79000
39000

Self Learning

  • 1 Year Access to Elearning content
  • 3 Months of Live Project Mentoring
44000
22000

About Machine Learning Course in Kochi

Kochi is one of the leading Information Technology cities in India, the information technology companies have fair future in the city. The city has 15 Gbit/s transfer speed and lower operational expenses contrasted with other significant urban areas in India. The Government advocate Info Park for several IT Companies. The Hi-tech campus called 'expected' expected to support soon. There is a huge number of Companies related to IT and ITES.

The IT and ITES related industries are flourishing in Kochi. Accessibility of modest transfer speed through undersea links and lower operational expenses contrasted with other significant urban communities in India has been to further its potential benefit. Different innovation and mechanical grounds including the administration advanced InfoPark, Cochin Special Economic Zone and KINFRA Export Promotion Industrial Park work in the edges of the city. Several new industrial campuses are under construction in the outskirts of the city.

DataMites™ Machine Learning Course in Kochi will allow you to dive deep into the Machine Learning concepts in an organized way. We offer it as a complete course covering both the intensive training sessions plus hands-on labs for the following in-demand topics

1. Python for Machine Learning,

2. Machine Learning Associate,

3. Machine Learning expert,

4. Time series foundation,

5. Model deployment (Flask-API),

6. Deep Learning -CNN Foundation,

DataMites™ Machine Learning training is conducted in Kochi as a 2months/64 hours duration course in a well-structured three phase module.

The structured three phase module of this course are

Phase 1 (15 Days)

Pre-course study helps you to develop your knowledge on the introduction of Machine Learning. It is a self-study phase that needs to be completed before entering to phase 2 module. Phase 1 includes high-quality videos, E-books covering the syllabus of Machine Learning essentials and Practice Materials. Furthermore, it facilitates the candidates to practice scripts at a cloud lab conveniently.

Phase 2 (2 Months)

This is the most crucial part of the training that comes with fulltime intensive training sessions through any of the convenient channels, Traditional Classroom Training, Live Instructor-Led Online Training, and Self Paced Learning / E-learning. This phase covers the next higher level syllabus of Machine Learning Associate and expert.

Phase 3 PAT Services (4 Months)

This is a dedicated part for candidates to make them market ready after the series of intensive coaching and learning. It covers 4-month Project Mentoring, exposure to 5+ detailed Industry related projects, revision sessions, access to an extensive collection of interview questions, resume support, mock interview sessions, job updates and experience certificate.

On completion of these well-orchestrated series of DataMites™ Machine Learning phases allow the aspirants to explore heights in their Machine Learning career.

SmartCity at Kakkanad is one of the prominent projects. Cyber City at Kalamassery is another integrated IT township SEZ being planned in the private sector. Cyber City at Kalamassery is another unified IT township SEZ being planned in the private sector.

Kochi is the Commercial city of Kerala state in India is the notable place for business in many sectors and located in the coastal. Foreign and domestic companies settled

their branches including IT Companies which build in Kochi itself.

The Key Features of Machine Learning Training in Kochi

Project Mentoring: You can gain experience by working on live projects from global AI and ML Solution providers.

Revision Sessions: Lots of revisions and multiple opportunities to clarify your doubts with our chief Data Scientist even after course completion.

Resume Support: You can curate a customized resume at the hands of experts to make your first impression the best one.

Interview Questions: Equip yourself with the latest interview questions and answers to face the interviews confidently.

Mock Interviews: Our experts will help you to increase your job interview success rate and get hired quickly by practicing numerous mock interview sessions.

Job Updates: All latest job updates which are validated and perspective are posted regularly by PAT Team in PAT Facebook group.

The prospects for Machine Learning is seeing an increasing curve and beginning a career in ML needs an intensive training from a recognized training provider. DataMites™ is India's top-ranked training provider, accredited by IABAC, delivering different training courses on Machine Learning in various cities in India. With at least two batches starting every month, the aspiring professionals can easily enroll for classroom or online ML course in Kochi with DataMites™.

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Machine Learning Training Syllabus & Schedules in Kochi

DESCRIPTION

Machine Learning (ML) is a different approach where computer learns the rules of solving complex problems without explicitly programmed. Machine Learning algorithms are at the core and important piece of data science.

 

Machine Learning Expert Course is designed in accordance with IABAC™ (International Association of Business Analytics Certifications) to provide a theory and application of popular Machine Learning algorithms in Supervised, Unsupervised and Deep Learning. Major algorithm are discussed in more details about how they work and apply these algorithms with realworld data.

 

Finally, we create ML models with Python Scikit-Learn package in solving business problems and case studies. This will give you a complete knowledge on Machine Learning algorithm, how they work, how to optimize, advantages and disadvantages of each algorithm along with practical application.

  • Detailed Knowledge of popular Machine Learning algorithms: Supervised and Unsupervised
  • Designing Machine Learning models from scratch to solve business problems with real world data
  • Python Machine Learning package - Scikit-Learn
  • Creating Machine Learning models with various ML algorithms and optimizes parameters for best performance
  • Introduction to Deep Learning
  • Preparing for IABAC™ Certification Exam
  • Basic Statistics Knowledge
  • Basic Python programming along with knowledge on Python packages Numpy and Pandas
  • Machine Learning Foundation course from IABAC or similar demonstrable ML skills.

In recent years, Machine Learning has taken over a mainstream business and evolved has a career track by itself. A quick search in job portals reveals about 20,000 Machine Learning job opportunities on a daily basis in the USA alone. This course provides you with practical knowledge in Machine Learning on choosing ML algorithms to optimization Machine Learning models, which enables to deliver data science projects effectively.

This course is an expert level course and candidate seriously pursuing a career in Data Science can opt.

 

  • Professionals aspiring to pursue a career in Machine Learning or Data Science in general
  • Fresh colleague graduates with basic Machine Learning knowledge, who are looking to gain more expertise
  • Candidates pursuing Data Scientist tracks

This course provides an expert level knowledge in Machine Learning opening a world of opportunities in the domain of Data Science, Artificial Intelligence, Robots, etc. This course enables candidates to further master the topic with various real-world project available in crowd sourced platforms such as Kaggle. As a part of the course, a certification assessment is conducted and candidate achieving minimum qualifying score receive a global certification, carrying immense value of the testimony of Expert Level ML knowledge.

At DataMites™, we truly believe and very excited about this big wave of Data Science. DataMites™ work with globally renowned Machine Learning experts in designing as well delivering a training course. There are millions of jobs and business opportunities in Data Science across the globe as of today and this is only going to increase exponentially in coming years.

 

DataMites is founded by a group of passionate Data Science evangelists with decades of experience in Analytics, big data and Data Science working with fortune 100 companies, across the globe. The mission of DataMites™ is to enable data science professionals with strong data science skills aligned to market requirements and be a part of this phenomenal Data Science era.

 

  • PASSIONATE: We are passionate in enabling professionals with best practice Data Science skills
  • ACCREDITED: DataMites™ is accredited with "International Association of Business Analytics Certifications (IABAC™)", aligning the syllabus with global market requirements
  • HANDS ON PROJECTS: On course completion, worthy candidates are involved in consulting assignments at building block levels to provide real-time exposure, thus supporting them to gain the confidence to work in real-world Data Science projects
  • JOB ASSISTANCE: A dedicated team, Placement Assistance Team (PAT), is tasked to assist candidates in preparing for the first Data Science job and mapping the job requirements to the individual candidate profile.
  • FLEXIBLE LEARNING: DataMites™ provides flexible learning options from traditional classroom to Virtual classroom, Instructor led online and self-learning.
  • LIBRARY: A Data Science library with a collection of valuable Data Science books and publications, assisted check-in/check-out options.
  • DATA SCIENCE LAB: Access to Cloud Data S

Since the IT companies are using AI and Machine Learning for almost every department, the scope for a Machine Learning professional is high. And the recent statistics also shows the high increase in the salary for an AI and Machine Learning professional. Companies like Infosys, Wipro, Dell, EY etc have been recruiting Machine Learning and AI Professionals for most of their Data Science jobs.

 

Since Kochi is one of the leading Information Technology cities in India, the information technology companies have fair future in the city. The Government promoted InfroPark for several IT Companies. The Hi-tech campus called ‘Smart City SEZ’ expected to service soon. There are hundreds of Companies which related IT and ITES.

 

The IT and ITES related industries are growing up in Kochi. This paved a great way for Machine Learning and AI. The increase in the Company adopting Machine Learning provides Job opportunities for the Professionals.

Syllabus

The following topics are covered here

Module 1 - Introduction to Data Science with Python

  • Installing Python Anaconda distribution
  • Python native Data Types
  • Basic programing concepts
  • Python data science packages overview

Module 2 - Python Basics: Basic Syntax, Data Structures

  • Python Objects
  • Math & Comparision Operators
  • Conditional Statement
  • Loops
  • Lists, Tuples, Strings, Dictionaries, Sets
  • Functions
  • Exception Handling

Module 3 - Numppy Package

  • Importing Numpy
  • Numpy overview
  • Numpy Array creation and basic operations
  • Numpy Universal functions
  • Selecting and retrieving Data
  • Data Slicing
  • Iterating Numpy Data
  • Shape Manupilation
  • Stacking and Splitting Arrays
  • Copies and Views : no copy, shallow copy , deep copy
  • Indexing : Arrays of Indices, Boolean Arrays

Module 4 - Pandas Package

  • Importing Pandas
  • Pandas overview
  • Object Creation : Series Object , DataFrame Object
  • View Data
  • Selecting data by Label and Position
  • Data Slicing
  • Boolean Indexing
  • Setting Data

Module 5 - Python Advanced: Data Mugging with Pandas

  • Applying functions to data
  • Histogramming
  • String Methods
  • Merge Data : Concat, Join and Append
  • Grouping & Aggregation
  • Reshaping
  • Analysing Data for missing values
  • Filling missing values: fill with constant, forward filling, mean
  • Removing Duplicates
  • Transforming Data

Module 6 - Python Advanced: Visualization with MatPlotLib

  • Importing MatPlotLib & Seaborn Libraries
  • Creating basic chart : Line Chart, Bar Charts and Pie Charts
  • Ploting from Pandas object
  • Saving a plot
  • Object Oriented Plotting : Setting axes limits and ticks
  • Multiple Plots
  • Plot Formatting : Custom Lines, Markers, Labels, Annotations, Colors
  • Satistical Plots with Seaborn

Module 7 - Exploratory Data Analysis: Case Study

The following topics are covered here

Module 1: Introduction to Statistics

  • Two areas of Statistics in Data Science
  • Applied statistics in business
  • Descriptive Statistics
  • Inferential Statistics
  • Statistics Terms and definitions
  • Type of Data
  • Quantitative vs Qualitative Data
  • Data Measurement Scales

Module 2: Harnessing Data

  • Sampling Data, with and without replacement
  • Sampling Methods, Random vs Non-Random
  • Measurement on Samples
  • Random Sampling methods
  • Simple random, Stratified, Cluster, Systematic sampling.
  • Biased vs unbiased sampling
  • Sampling Error
  • Data Collection methods

Module 3: Exploratory Analysis

  • Measures of Central Tendencies
  • Mean, Median and Mode
  • Data Variability : Range, Quartiles, Standard Deviation
  • Calculating Standard Deviation
  • Z-Score/Standard Score
  • Empirical Rule
  • Calculating Percentiles
  • Outliers

Module 4: Distributions

  • Distribtuions Introduction
  • Normal Distribution
  • Central Limit Theorem
  • Histogram - Normalization
  • Other Distributions: Poisson, Binomial et.,
  • Normality Testing
  • Skewness
  • Kurtosis
  • Measure of Distance
  • Euclidean , Manhattan and Minkowski Distance

Module 5: Hypothesis & computational Techniques

  • Hypothesis Testing
  • Null Hypothesis, P-Value
  • Need for Hypothesis Testing in Business
  • Two tailed, Left tailed & Right tailed test
  • Hypothesis Testing Outcomes : Type I & II erros
  • Parametric vs Non-Parametric Testing
  • Parametric Tests , T - Tests : One sample, two sample, Paired
  • One Way ANOVA
  • Importance of Parametric Tests
  • Non Parametric Tests : Chi-Square, Mann-Whitney, Kruskal-Wallis etc.,
  • Which Test to Choose?
  • Ascerting accuracy of Data

Module 6: Correlation & Regression

  • Introduction to Regression
  • Type of Regression
  • Hands on of Regression with R and Python.
  • Correlation
  • Weak and Strong Correlation
  • Finding Correlation with R and Python

The following topics are covered here

Module 1: Machine Learning Introduction

  • What is Machine Learning
  • Applications of Machine Learning
  • Machine Learning vs Artificial Intelligence
  • Machine Learning Languages and platforms
  • Machine Learning vs Statistical Modelling

Module 2: Machine Learning Algorithms

  • Popular Machine Learning Algorithms
  • Clustering, Classification and Regression
  • Supervised vs Unsupervised Learning
  • Application of Supervised Learning Algorithms
  • Application of Unsupervised Learning Algorithms
  • Overview of modeling Machine Learning Algorithm : Train , Evaluation and Testing.
  • How to choose Machine Learning Algorithm?

Module 3: Supervised Learning

  • Simple Linear Regression : Theory, Implementing in Python (and R), Working on use case.
  • Multiple Linear Regression : Theory, Implementing in Python (and R), Working on use case.
  • K-Nearest Neighbors : Theory, Implementing in Python (and R), KNN advantages, Working on use case.
  • Decision Trees : Theory, Implementing in Python (and R), Decision |Tree Pros and Cons, Working on use case.

Module 4: Unsupervised Learning

  • K-Means Clustering: Theory, Euclidean Distance method.
  • K-Means hands on with Python (and R)
  • K-Means Advantages & Disadvantages

The following topics are covered here

Module 1: Advanced Machine Learning Concepts

  • Tuning with Hyper parameters.
  • Popular ML algorithms,
  • Clustering, classification and regression,
  • Supervised vs unsupervised.
  • Choice of ML algorithm
  • Grid Search vs Random search cross validation

Module 2: Principle Component Analysis (PCA)

  • Key concepts of dimensionality reduction
  • PCA theory
  • Hands on coding.
  • case study on PCA

Module 3: Random Forest - Ensemble

  • Key concepts of Randon Forest
  • Hands on coding.
  • Pros and cons.
  • case study on Random Forest

Module 4: Support Vector Machine (SVM)

  • Key concepts of Support Vector Machine.
  • Hands on coding.
  • Pros and Cons.
  • case study on SVM

Module 5: Natural Language Processing (NLP)

  • Key concepts of NLP.
  • Hands on coding.
  • Pros and Cons.
  • Text Processing with Vectorization
  • Sentiment analysis with TextBlob
  • Twitter sentiment analysis

Module 6: Naïve Bayes Classifier

  • Key concepts of Naive Bayes.
  • Hands on coding.
  • Pros and Cons
  • Naïve Bayes for text classification
  • New articles tagging

Module 7: Artificial Neural Network (ANN)

  • Basic ANN network for Regression and Classification
  • Hands on coding.
  • Pros and Cons
  • Case study on ANN, MLP

Module 8: Tensorflow overview and Deep Learning Intro

  • Tensorflow work flow demo
  • Introduction to deep learning.

Module 1: Tableau Introduction

  • Tableau Interface
  • Dimensions and measures
  • Filter shelf
  • Distributing and publishing

Module 2: Connecting to Data Source

  • Connecting to sources, Excel, Data bases, Api , Pdf
  • Extracting and interpreting data.

Module 3: Visual Analytics

  • Charts and plots with Super Store data

Module 4: Forecasting

  • Forecasting time series data

Module 1: Understanding Business Case

  • Components of Business Case.
  • ROI calculation techniques.
  • Scoping

Module 2: Writing Data Science Business Case

  • Defining Business opportunity.
  • Translating to Data Science problem.
  • Creating project plan

Module 3: Benefits Analysis

  • Demonstrating break even and benefits analysis with Data Science Solutions.
  • IRR benefits analyis
  • Discounted Cash Flow

Module 4: Starting project, Setting up Team and closing

  • Initiating Project
  • Setting up the Team
  • Controling project delivery
  • Closing project.

FAQ'S

DataMites™ provide flexible learning options from traditional classroom training, latest virtual live classroom to distance course. Based on your location preference, you may have one or more learning options

This course is perfectly aligned to the current industry requirements and gives exposure to all the latest techniques and tools. The course curriculum is designed by specialists in this field and monitored improved by industry practitioners on a continual basis.

All certificates can be validated with your unique certification number at IABAC.org portal. You also get candidate login at exam.iabac.org, where can find your test results and other relevant validation details.

The results of the Exam are immediate if you take an online test at exam.iabac.org portal. The certificate issuance, as per IABAC™ terms takes about 7-10 business days for e-certificate.

No, the exam fees are already included in the course fee and you will not be charged extra.

Course fee needs to be paid in one payment as it is required to block your seat for the entire course as well as book the certification exams with IABAC™. In case, if you have any specific constraints, your relation manager at DataMites™ shall assist you with part payment agreements

DataMites™ has a dedicated Placement Assistance Team(PAT), who works with candidates on an individual basis in assisting for the right Data Science job.

You get 100% refund training fee if you the training is not to your satisfaction but the exam fee will not be refunded as we pay to accreditation bodies. If the refund is due to your availability concerns, you may need to talk to the relationship manager and will be sorted out on case to case basis

DataMites™ provides loads of study materials, cheat sheets, data sets, videos so that you can learn and practice extensively. Along with study materials, you will get materials on job interviews, new letters with latest information on Data Science as well as job updates.

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