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Data Science Course in Malayalam

Do you have a language barrier to understanding technical concepts in data science and machine learning? Join our online Data Science course in Malayalam to kickstart a high-paying career this year! Learn programming, data analysis, visualization, MySQL, and machine learning in Malayalam

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Overview Of Data Science Course in Malayalam

Entri's Data Science and Machine Learning course lets you get started in this amazing subject of yours. This online education teaches you all you need to know, whether you're a beginner or want to improve. With engaging videos, conversations, and one-on-one assistance, mastered the fundamentals of Python, statistics, data analysis, machine learning, and data visualization. Use Entri's career help to prepare for real-world employment by putting what you study into practice through practical projects. After finishing your studies, you'll even receive certificates recognized by Illinois Tech.

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Inclusive & Immersive Hybrid Training Sessions

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Industry Expert Sessions

80+ Live & Recorded Sessions Icon

80+ Live & Recorded Sessions

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Soft Skill Sessions

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Industry Networking

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Placement Training

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Illinois Tech Certification

Skills Covered

These are the most important skills to have if you want to succeed in the data science and machine learning fields.

Placement Stories

Here is our aspirants achievements to inspire you

Why Do Students Love Us?

Hear from Our Data Science Students!

Tools Covered

Illuminate the path to insights! Unlock the power of data science and machine learning with these necessary tools!

Data Science Job Roles

What Exactly Does a Data Scientist Do? Lets Dive Deep into Roles!

Data Scientist

To find patterns and trends in massive data sets, a data scientist gathers, examines, and interprets the information. To glean insights and make data-driven decisions, they employ a range of instruments and methodologies. People may become qualified for this position by taking a course in data science and machine learning, which will teach them statistical analysis, computer languages, and data mining.

Machine Learning Engineer

The goal of machine learning engineers' work is to create models and algorithms that let computers learn from data and make precise predictions. These experts have a solid foundation in data science, programming, and mathematics. People who take courses in data science and machine learning can prepare for this position by gaining a strong foundation in these fields.

Data Analyst

Data analysts collect, arrange, and evaluate data to give firms valuable insight. They convey their results to important stakeholders after identifying trends and patterns using statistical tools and procedures. People who have taken a course in data science and machine learning and are proficient in analytics, visualization, and data manipulation are ideal candidates for this position.

Business Intelligence Analyst

Analysts of business intelligence are in charge of examining data to find patterns and trends that can help businesses make wise decisions. To gather information from several data sources and display it in a way that stakeholders can understand, they make use of a range of data analytics technologies. Strong analytical skills, business knowledge, and outstanding communication ability are required for this role.

Curriculum

The curriculum is designed to help you learn the skills required to become a successful professional.

  1. Introduction to Programming
  • What is programming?
  • Compiler,Interpreter
  • Source Code
  • Machine code
  • Algorithms
  • Editors
  1. Introduction to Data Science
  • What is Data Science?
  • Job Roles
  • Terminologies
  • Data Science Applications and its work flows

  1. Language Introduction and Installation
  • Python history
  • Python features
  • python and pycharm installation.
  1. Python Basics
  • Print command
  • Comments,escape sequences
  • Variables
  • Data types
  • User interactive command, operators
  1. Conditional and looping statements
  • Selection statements
  • Control statements
  • Break and continue statements
  • Nested loops
  1. Data Structures in python

Introduction to user defined data structures and non-primitive data structures:list,

dictionaries, set,tuples, strings and sequences,accessing and modifying elements in data

structures,comprehension: list, set and dictionary.

  1. Functions in Python

Defining functions, passing arguments to functions, different types of arguments, returning

values from functions, local and global namespace, lambda function, recursion, filter,

map,reduce, eval. Generators and decorators.

  1. File Handling and Exception Handling

File processing, Reading and writing files using ‘with’ statements. What is an Exception?,

raising and catching exceptions and handling errors gracefully using try-catch-finally.

  1. Object Oriented Programming

Introduction to OOPs, Classes and objects, inheritance and polymorphism, encapsulation

and abstraction.

  1. Modules in Python

Introduction to modules, importing modules, creating and using modules.

  1. Regular Expressions

Defining regular expressions, using regular expressions with python.

10.Pandas and Numpy

Introduction to Pandas library, reading and writing data with pandas, data cleaning and

exploration with pandas. Introduction to numpy, numpy basic operation.

  1. Data Visualization with Matplotlib and seaborn

Introduction, basic and advanced plotting technique

  1. Introduction to SQL
  • Introduction to databases and database management system
  • Overview of MySQL
  • Installing and getting started with MySQL workbench.
  1. SQL Database
  • Creating databases
  • Dropping databases
  • Introduction to tables
  • Data types in MySQL
  1. Data Definition Language
  • Introduction DDL commands
  • Creating table
  • Modifying table using ALTER, DROP, TRUNCATE, RENAME
  1. Data Manipulation Language
  • Overview of MySQL SELECT statement
  • Retrieving data
  • Filtering and sorting
  • Joining and combining data
  • Updating and deleting data
  • Inserting data
  • Constraints(PRIMARY KEY, FOREIGN KEY, UNIQUE, NOT NULL.
  1. MySQL Functions and Joins

MySql built-in functions, inner, outer and self joins and combining data from multiple tables.

  1. MySQL subqueries and views

Subqueries and nested queries,creating and using views, normalization and denormalization

  1. MySQL stored procedures and triggers

Creating and using stored procedures and triggers, database security and user management.

Project

Build a simple database to help us manage the booking process of a sports complex. The sports complex has the following facilities: 

  • 2 tennis courts
  • 2 badminton courts,
  • 2 multi-purpose fields
  • 1 archery range.

Each facility can be booked for a duration of one hour. Only registered users are allowed to make a booking. After booking, the complex allows users to cancel their bookings latest by the day prior to the booked date. Cancellation is free. However, if this is the third (or more) consecutive cancellations, the complex imposes a $10 fine

  1. PowerBI Introduction
  • Introduction
  • PowerBI
  • Power query editor
  • PowerBI service, 
  • Installation and configuration of powerBI desktop
  • Connecting to data sources and loading data
  1. Data modeling in PowerBI

Understanding data modeling and relationships creating relationships between tables, building hierarchies and calculated columns, transforming using power query.

  1. Data Visualization in PowerBI

Understanding data visualization best practices, building basic visualizations(charts, graphs, tables etc..), formatting and customizing visualizations.

  1. Building Interactive reports 

Using filters and slicers to create interactive reports, building drill-through reports and drill-down visualizations, creating bookmarks and scenarios.

  1. Creating Dashboards

Building dashboards with multiple visualizations, creating dashboards tiles and adding images, creating custom visuals using powerBI

  1. Data Analytics with PowerBI 

Understanding data analytics and DAX language, creating DAX formulas and measures.

  1. Project

Financial Performance analysis: to optimize financial reporting in a firm that provides customers to track their financial health and productivity. Create data models and visualizations, and dashboards and present the project results and insights.

  1. Probability & Statistics

Definition of probability,conditional probability,independent events, Bayes' rule, Random variables, discrete random variable, continuous random variable, probability density function, mean, median, mode, Standard deviation, correlation, correlation coefficient. Testing of hypothesis, confidence interval, Chi-squared test, t-test

  1. Introduction to Machine Learning

Machine learning concepts and applications,Overview of Supervised, Unsupervised, and Reinforcement learning.Exploring common machine learning algorithms

  1. Data Preprocessing for Machine Learning

Types of Data: Categorical and Numerical Data, Understanding data preprocessing and its importance in machine learning, Handling missing data, outliers, and categorical variables, Label Encoding, Feature scaling and normalization techniques.Python Library: Numpy, Pandas, Sklearn

  1. Project

Use a dataset then remove NaN values and apply label encoder and scaling methods.

  1. Supervised Learning : Regression

Understanding regression analysis and its use in machine learning, Building linear regression models,

Evaluating model performance and making predictions.

  1. Project using Regression

Create a model using Linear regression algorithms and predict using the best algorithm among them.

  1. Supervised Learning

Classification Understanding classification analysis and its use in machine learning, Building logistic regression, Support Vector Machines, Random Forest, K-Nearest Neighbor, Naïve Bayes and Decision tree models. Evaluating model performance using different classification accuracy metrics and making predictions.

  1. Project

Create a model using different algorithms for a given dataset and choose the best algorithm among them.

  1. Unsupervised Learning

Clustering Understanding clustering analysis and its use in machine learning, Building k-means and hierarchical clustering models,Evaluating model performance and making predictions,

  1. Project

Create a model using different algorithms and predict using the best algorithm among them.

  1. Unsupervised Learning

Dimensionality Reduction Understanding dimensionality reduction and its use in machine learning, Building principal component analysis (PCA) and t-SNE models, Evaluating model performance and making predictions.

  1. Natural Language Processing

Basic concept of NLP, Data Cleaning: remove punctuations, tokenization, remove stop words, stemming, lemmatization.Packages of NLP : NLTK (Natural Language ToolKit), Pattern, TextBlob,Vectorization techniques: Bag of Words, TF-IDF

  1. Project

For the given paragraph do the following: word_tokenise and sent_tokenise, using stop words eliminate most common words and do stemming and lemmatization.

Deep learning basics: Neural Network, perceptron,Back-Propagation, Activation functions, Deep networks, Regularization, Dropout, Batch Normalization.Python libraries for Deep learning : Keras, Tensor flow. Convolutional neural networks: Introduction to CNNs, Convolution, Correlation, FIltering. CNN architectures, Compiling and fitting a model Advanced Deep architectures:Recurrent Neural networks (RNNs), Advanced RNN: LSTM

Project

Create a deep network model using CNN and calculate its accuracy and loss values.

Data Science Blogs

Explore Trending Topics of Data Science and Machine Learning

Top Data Science Certifications For 2024

Are you looking for an appealing job opportunity in 2024? Then, one of your finest possibilities should be data science. The data science sector is expanding quickly, and it is reasonable to consider it to be in the growth stage of the product life cycle. Here are the List of Top Data Science Certification for 2024

Data Science vs Data Mining : Comparison Guide

Data mining is the process of analyzing data and extracting helpful information, while data science involves obtaining valuable insights from structured and unstructured data using various tools and techniques. Let's read more about this!

Data Scientist vs Cyber Security: Which Career is Best?

Cyber security and data science offer incredible opportunities for individuals with technological skills and knowledge and those who want to get involved in exciting and active IT fields.

Best Places to Host Data Science Portfolio

As a data scientist, you should have a professional portfolio that demonstrates your abilities and expertise. Possessing a portfolio facilitates the process of informing prospective employers about your experience and credentials. It also facilitates sharing your work and showcasing your accomplishments.

Eligibility / Pre-requisities

Anyone with an interest in data science and machine learning can enroll in these courses. There is no specific educational background required. However, a basic understanding of mathematics, statistics, and programming can be beneficial.

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Logical thinking

Having the ability to think critically and approach problems analytically by identifying its key components, and understanding how they relate to each other.

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Basic Programming Skills

Analyzing and interpreting complex datasets, developing machine learning models, and providing actionable insights to solve business problems.

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Problem-Solving Skills

Formulate data-driven solutions, identify patterns and trends, and ability to apply logical thinking to solve complex problems with strong problem-solving and analytical skills.

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Basic Mathematical skills

Mastering fundamental mathematical concepts, like algebra, calculus, and probability, is essential. These concepts serve as building blocks in data science and are applicable in various fields.

Our Hiring partners

To help companies reach their recruiting targets, provide them with access to a global network of recruitment partners.

Why Live Sessions?

Live sessions on data science and machine learning have several advantages that make them a valuable learning resource.

Live Sessions

Increased Engagement

Engage participants directly, respond to inquiries promptly, and provide a more dynamic learning environment.

Real-time Q&A

This feature creates a lively learning atmosphere by allowing participants to ask questions and get prompt responses.

Clarification of doubts

Prompt answers from the teacher help clear up confusion and reinforce comprehension.

Flexible scheduling

Live and recorded session options accommodate a range of schedules and time zones.

Immediate feedback

Participants may provide instructors with comments immediately, enabling them to make changes and enhance the course in real-time.

Your Data Science Course Mentors

Reach out to our team of professionals to get a professional edge; they will offer priceless advice and assistance. Discover our group of mentors!

Data Science Intructors

Unlock your professional potential by finding the key! Get the skills and information you need to succeed in this industry by getting to know our data science and machine learning specialists.

Data Science and Machine Learning Certifications

Courses Recognised by

illinois Tech Certification
NSDC

Frequently Asked Questions

Illinois certification validates your proficiency and expertise across various industries. It can enhance your credibility and positively impact your career growth, earning potential, and professional fulfillment. Obtaining Illinois certification opens up opportunities for career advancement and high-paying jobs, bringing ample career opportunities and enhancing your professional success.

Illinois certification is best for IT freshers. This certification program provides comprehensive training and education on various aspects of IT, including programming languages, software development, database management, and more.

Illinois certification helps freshers build a strong foundation in IT. It equips them with the necessary skills to succeed in their careers and to get better job opportunities with higher salaries.

Course Review

Enrolled by Students
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Key Learning Outcomes

The following are the main points that were learned during the 'Entri Elevate Data Science of Machine Learning' course in Malayalam:

Data Wrangling & Cleaning

To prepare jumbled data for analysis, master data manipulation techniques.

Statistical Analysis

Comprehend fundamental statistical principles to analyze information and derive significant conclusions.

Machine Learning Fundamentals

Learn the fundamentals of machine learning, including the various applications of these methods.

Data visualization

Produce eye-catching images to convey data insights clearly.

Problem-Solving Method

To tackle challenging issues, use a data-driven methodology.

Learn to Creat Models

Create models with the ability to forecast trends and use them to address business issues.

Utilize cutting-edge machine learning algorithms

Utilize cutting-edge machine learning algorithms to provide answers for actual business issues.

Create an AI strategy

Create an AI strategy tailored to your sector and assess the different aspects of its execution.

Live Sessions

Data Science Course in Malayalam- Frequently Asked Questions

Yes! This course is specially designed for the candidates from Kerala region. So, the primary medium of communication will be in Malayalam.

After you complete the data science and machine learning course in Malayalam, some of the career paths you can follow are Data Scientist, Data Engineer, Data Analyst, Machine learning Engineer, Marketing Analyst, Clinical Data Manager, Business IT Analyst. Apart from these, there are other options too, like Data Visualization Specialist, Artificial Intelligence Engineer, Data Product Manager, Data Marketing Analyst etc. In conclusion, the career opportunities in data science are vast and varied, and it largely depends on your interests, skills, and the type of industry you want to work in. Click the link below & check the wide range of career options available in Kerala- Data Science Jobs in Kerala

The salary of a data scientist can vary on several factors like experience, qualifications, and the type of company they work for. As per the recent salary surveys, the average salary for data scientists in Kerala is around 8 to 15 lakhs per annum.

Data science plays a critical role in helping companies make informed decisions based on data, and it is being applied in many industries, including healthcare, finance, retail, and technology. With the rise of big data and the increasing importance of data-driven decision-making, data science is poised for even greater growth and impact in the coming years. According to the US Bureau of Labor Statistics, the demand for Data Science jobs is expected to grow by 27.9 per cent by 2026 and 36% growth by 2031.

Of course! If you are planning to migrate from India to other countries, upskilling yourself in data science will be a true blessing. In Europe, countries such as the United Kingdom, Germany, and France have strong economies and a growing demand for data scientists. So, you will be able to get into a high-paying career anywhere in the world

The Data Science course in Entri App is an online programme designed to provide a comprehensive understanding of Data Science and related technologies, such as Python, statistics, data analysis, machine learning, and Tableau. The course includes live projects and capstone projects to give you real-world experience in the field.

Preparatory Session for Programming Python Programming Data Analysis & Visualization MySQL Machine Learning with Python Deep learning Fundamentals Capstone Projects

Yes, Entri App provides career support through Job opportunities portal to explore job options Personalised industry mentorship for career guidance Resume Review Live profile-building workshops

Of Course! Our data science course is designed for beginners as well. The session covers all the fundamentals to put you on track.

Certainly, Entri App provide the option of part-time or online data science courses, allowing individuals to pursue them while managing their work or other obligations.

Having a degree in computer science is not always a strict requirement. Numerous data science programs welcome students from various educational backgrounds, provided they fulfill the necessary prerequisites.

Indeed, Kerala's IT sector, healthcare industry, and e-commerce businesses are experiencing an increasing need for data scientists. Additionally, you can consider exploring remote job prospects with global companies

Advantages of Learning from Entri

Elevate Learning Experience

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Student Support

Available all-day, using Slack for urgent queries.

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Q&A Forum

Timely doubt resolution from peers and mentors

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Expert Feedback

Personalized feedback on assignments and projects

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Industry Networking

Live doubt clearing sessions with Industry Experts

Career Support

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Personalized Industry Mentorship

Get mentored by an experienced data science expert and receive personalized feedback for better career guidance

Resume Review Icon

Resume Review

Obtain specific, personalized inputs on your resume structure and content

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Live profile-building workshops

Be it your resume, GitHub, or Kaggle, build your profile with hands-on sessions

Elevate Coding Webinars

Who Can Apply for this Data Science Course

  • Students
  • Professionals
  • Career Switchers
  • Job Seekers
  • House Wife
  • Unemployers
  • Freelancers
Who can apply
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