Machine Learning with Python

BY
DataMites

Get a deeper understanding of topics related to Machine Learning by pursuing the certification of Machine Learning with Python by DataMites.

Mode

Online

Duration

5 Months

Fees

₹ 37900 48000

Quick Facts

particular details
Medium of instructions English
Mode of learning Self study, Virtual Classroom +1 more
Mode of Delivery Video and Text Based

Course overview

The Machine Learning with Python certification course is an online/offline programme that deals with the topics of Machine Learning. Participants who join the course will gain insights into Machine Learning with Python. Students get the chance to get trained through some of the expert trainers in the course. 

The Machine Learning with Python certification syllabus of the programme is curated by industry professionals and can be completed in a minimum of five months. The self-paced course includes fundamentals as well as case studies within the curriculum. The Machine Learning with Python online course does not require aspiring students to go through any entrance exam to get into the course. Students can achieve a certificate upon the completion of the programme after passing the exam.

The highlights

  • 3 different modes of learning- Blended learning, Classroom training and Live virtual classes
  • 5 months course
  • 350 hours of learning
  • 100 hours live online training
  • 1 year of self-learning and live mentoring
  • Placement services
  • Accredited by IABAC
  • Certification is provided at the end by DataMites
  • Cloud lab access in Classroom training
  • 20 Capstone and 1 client project in every mode of learning

Program offerings

  • Videos
  • Projects
  • Case studies
  • Cheatsheets
  • Data set
  • Blended
  • Online
  • Newsletter
  • Internship.

Course and certificate fees

Fees information
₹ 37,900  ₹48,000

Machine Learning with Python Fees Details

Heads 

Mode of learning 

Amount 

Course fee

Live virtual 

Rs. 48,000 

Blended learning 

Rs. 29,000

Classroom 

Rs. 60,000 

certificate availability

Yes

certificate providing authority

IABAC

Who it is for

The Machine Learning with Python by Datamites is apt for the following people-

  • Participants who want to grow as a professional in the discipline of Data Science and machine learning
  • Graduates or Freshers 
  • Professionals pursuing Data scientist tracks 

Eligibility criteria

Work Experience

Candidates who have hands-on coding experience of popular Machine Learning algorithms on classic data sets are preferred. 

Education

Candidates need to have a basic understanding of programming and statistics.

Certification Qualifying Details

Candidates can achieve the certification of Machine Learning with Python training after acquiring passing grades in the exam. It is essential to complete the entire programme successfully. 

What you will learn

Machine learning Knowledge of python Knowledge of algorithms Statistical skills

Participants will learn the following through the Machine Learning with Python certification

  • Candidates will learn about data selection and filtration. 
  • Students will gain an understanding of structures and conditional statements. 
  • Participants will learn how to process data for Machine Learning in the Machine Learning with Python programme.
  • Candidates will learn different machine learning algorithms.
  • Students will learn how to build machine learning models in Machine Learning with Python training.
  • Candidates will learn the difference between supervised and unsupervised machine learning.

The syllabus

Python for Machine Learning

  • Programming Basics
  • Python Data Types
  • Structures and conditional statements
  • Python core packages
  • Introduction to Jupyter Notebook
  • Introduction to Numpy and Pandas
  • Data filtering and selecting
  • Find duplicates and treating missing values
  • Concatenate and transform data

Basic statistics for Machine Learning

  • Basic Statistics and Exploratory Analysis
  • Descriptive summary statistics with Numpy
  • Summarize continous and categorical data
  • Outlier analysis

Introduction to Machine Learning

  • Overview of Supervised and Unsupervised Machine Learning
  • Linear Regression
  • Clustering with K-means
  • Naive Bayes Classification
  • Introduction to Neural Networks

Data processing for Machine Learning

  • Advanced Data Mugging
  • Outlier Analysis
  • Treating for missing values
  • Normalization vs Standardization of data

Machine Learning Algorithms

  • Supervised Machine Learning algorithms
  • K-Nearest Neighbors (KNN) concept and application
  • Naive Bayes concept and application
  • Logistic Regression concept and application
  • Classification Trees concept and application
  • Unsupervised Machine Learning algorithms
  • Clustering with K-means concept and application
  • Hierarchial Clustering concept and application

Building and training Machine Learning models

  • Setting up the project with ML workflow.
  • Data Preprocessing and statistical exploration
  • Building , Training and evaluation of Machine Learning Model

Hands-on case study: Property estimations with ML

  • Analysis the case study: Property Estimations
  • Setting up the project with ML workflow.
  • Data Preprocessing and statistical exploration
  • Choosing the Machine Learning Algorithm for this case
  • Building, Training and evaluation of Machine Learning Model

Admission details

Candidates need to follow the given instructions for the admission process- 

Step 1- Candidates can apply by visiting the official link.

Step 2- Candidates can click on the Enquire Now option.

Step 3- Candidates can contact the Relationship Manager and discuss the preferred course with them. 

Step 4- Candidates can join the course after paying the required amount of course fee. 

How it helps

The Machine Learning with Python online course imparts education that includes the topics of Machine Learning. The course can be completed within five months. The case studies and projects included in the programme allow the candidate to gain valuable practical insights into the relevant market. The certification achieved through the exam helps the students on a professional level. 

The Machine Learning with Python certification benefits ensures that students get a job opportunity as it makes them worthy of the opportunity. The candidate who gets certified through the course has more chances of getting an employment opportunity. Students will be able to understand the most important concepts of Machine Learning and Python and can apply for higher studies in the same specialization. 

Professionals who pursue the programme can get an increment or promotion in their organisation. They can also guide their juniors in case of any problem. Due to the great value of the certification in the global market, the profile of the candidate gets a boost. 

FAQs

What are the prior skills required for taking this course?

Students need to have basic programming and statistics skills along with some experience in coding ML algorithms.

Can I pursue the Machine Learning with Python certification course offline?

Yes, students can pursue the course in offline mode.

When will I get my certification?

Students will get their certificates only after getting passing grades in the exam.

Is the fee paid refundable?

Yes, students can get a refund for their course as per their guidelines. 

Does the programme include study material?

Yes, the course includes study material for the students.

Does the course provide university credits?

No, the online course does not provide any university credits. 

Is there any guarantee that I'll get placed after pursuing the course?

No, the Machine Learning with Python programme does not guarantee any job offer.

Will I be provided guidance regarding job hunting?

Yes, students will get step-by-step guidance and help to get a job or internship.

How many months will it take to complete the Machine Learning with Python certification syllabus?

The course will take a minimum of 5 months to one year to get completed, depending upon the type of mode of learning the student prefers.

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