Data Science Using Masters Program

Data Science using Masters Program Introduction

Introduction to the “Data Science Using Python Programming Course” at iMMEK Softech Academy

Comprehensive Curriculum: The “Data Science Using Python Programming Course” at iMMEK Softech Academy offers an in-depth exploration of Python for data science, covering essential libraries like NumPy, pandas, and Matplotlib.
Hands-On Learning: Gain practical experience through hands-on projects and real-world case studies, ensuring you can apply theoretical concepts effectively.
Expert Instructors: Learn from industry experts with extensive experience in data science and Python programming, providing personalized guidance and support.
Flexible Learning Options: Choose from online or in-person classes, with flexible schedules to accommodate working professionals and students.
Career Support: Benefit from iMMEK Softech Academy’s robust career services, including resume building, mock interviews, and job placement assistance.
Certification: Earn a recognized certificate upon completion, enhancing your resume and opening doors to various career opportunities in data science.

Enroll in the “Data Science Using Python Programming Course” at iMMEK Softech Academy to kickstart your data science career with comprehensive, hands-on training.

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Data Science using Python Programming Description

Data Science Using Python Programming Course at iMMEK Softech Academy

Introduction

Data science is a rapidly growing field that combines statistical analysis, machine learning, and data visualization to derive insights from large datasets. Python, with its simplicity and versatility, has become the go-to programming language for data scientists. The “Data Science Using Python Programming Course” at iMMEK Softech Academy provides a comprehensive and practical approach to mastering data science using Python. This course is designed to equip you with the skills needed to tackle real-world data challenges and advance your career in this dynamic field.

Tools Covered

The Data Science using Python Programming course at iMMEK Softech Academy covers a comprehensive range of tools essential for mastering the discipline. Students will gain proficiency in using Jupyter Notebook, an open-source web application that allows for interactive computing.

In the “Data Science Using Python Programming Course,” you will gain hands-on experience with a variety of powerful tools and libraries, including:

Python: The primary programming language used for data science.
NumPy: A fundamental package for numerical computing with Python.
pandas: A powerful data manipulation and analysis library.
Matplotlib and Seaborn: Libraries for data visualization.A
Scikit-learn: A library for machine learning and statistical modeling.
TensorFlow and Keras: Libraries for building and training deep learning models.
Jupyter Notebook: An interactive computing environment for writing and sharing code.
SQL: For database management and data querying.
Git and GitHub: Tools for version control and collaborative coding.

Pre-requisites

To ensure students can fully benefit from the Data Science using Python Programming course, certain prerequisites should be met. A basic understanding of programming concepts, including variables, loops, and functions, is essential. Familiarity with Python is highly recommended, although the course does provide an introductory overview for beginners.

To ensure you can make the most out of this course, it is recommended that you have:

Basic Programming Knowledge: Familiarity with any programming language (Python preferred).
Mathematics and Statistics: Understanding of basic concepts in mathematics and statistics.
Analytical Skills: Ability to analyze data and solve problems logically.

Objectives

The primary objectives of the Data Science using Python Programming course at iMMEK Softech Academy are to equip students with the necessary skills to handle and analyze large datasets effectively.

The “Data Science Using Python Programming Course” aims to:

Teach Python Programming: Equip you with a solid understanding of Python programming and its applications in data science.
Data Manipulation and Analysis: Enable you to manipulate, analyze, and visualize data using powerful Python libraries.
Machine Learning Techniques: Introduce you to various machine learning algorithms and techniques for predictive modeling.
Deep Learning Concepts: Provide a foundation in deep learning, including neural networks and advanced model building.
Real-World Applications: Apply data science techniques to real-world problems and datasets through hands-on projects.
Career Readiness: Prepare you for a career in data science with practical skills and industry-recognized certification.

Why Join This Course?

Joining the Data Science using Python Programming course at iMMEK Softech Academy offers numerous advantages. The curriculum is designed to cover all critical aspects of data science, providing a well-rounded education. Students will benefit from the expertise of experienced instructors who have extensive knowledge of Python and its applications in data science.

Practical Learning Experience

Hands-On Projects: Work on real-world datasets and projects that simulate industry scenarios.
Interactive Sessions: Engage in interactive coding sessions and practical exercises to reinforce learning.
Portfolio Development: Build a strong portfolio of projects to showcase your skills to potential employers.

Expert Instructors

Industry Experts: Learn from experienced instructors who are experts in the field of data science and Python programming.
Personalized Guidance: Receive personalized attention and support to address your learning needs and challenges.

Flexible Learning Options

Online and In-Person Classes: Choose between online and in-person classes to suit your schedule and learning preferences.
Flexible Timings: Attend classes at convenient times, including weekday and weekend batches.

Career Support

Job Placement Assistance: Benefit from comprehensive job placement services, including resume building, interview preparation, and job alerts.
Networking Opportunities: Connect with industry professionals, alumni, and peers through networking events and forums.

Why iMMEK Softech Academy Stands as a Premium Institute

iMMEK Softech Academy stands out as a premier institute for Data Science training due to several key factors. The academy offers state-of-the-art facilities, with modern classrooms and the latest technology and software. Partnerships with leading industry organizations provide students with valuable internship and employment opportunities, enhancing their practical experience and career prospects.

State-of-the-Art Facilities

Modern Classrooms: Learn in a state-of-the-art learning environment equipped with the latest technology.
Resource Access: Access a wealth of resources, including online libraries, research papers, and software tools.

Industry-Relevant Curriculum

Updated Content: Stay ahead with a curriculum that is regularly updated to reflect the latest industry trends and technologies.
Real-World Relevance: Study topics and techniques that are directly applicable to real-world data science challenges.

Strong Industry Connections

Partnerships and Collaborations: Benefit from iMMEK Softech Academy’s strong connections with leading companies and organizations in the industry.
Guest Lectures and Workshops: Gain insights from guest lectures and workshops conducted by industry leaders and experts.

Proven Track Record

Successful Alumni: Join a network of successful alumni who have gone on to work at top companies and organizations worldwide.
High Placement Rates: Enjoy high placement rates with many graduates securing positions in leading companies shortly after completing the course.

Detailed Course Outline

Introduction to Python Programming
- Python Basics: Syntax, variables, and data types
- Control Structures: Conditional statements and loops
- Functions and Modules: Defining and using functions and modules
Data Structures and Algorithms
- Lists, Tuples, and Dictionaries: Data structure manipulation
- Algorithms: Sorting and searching algorithms
Data Manipulation with pandas
- DataFrames: Creating and manipulating DataFrames
- Data Cleaning: Handling missing data and data transformation
Numerical Computing with NumPy
- Arrays: Creating and manipulating NumPy arrays
- Mathematical Operations: Performing mathematical operations on arrays
Data Visualization with Matplotlib and Seaborn
- Plotting: Creating various types of plots and charts
- Advanced Visualization: Customizing plots and creating interactive visualizations
Introduction to Machine Learning
- Supervised Learning: Regression and classification techniques
- Unsupervised Learning: Clustering and dimensionality reduction
Advanced Machine Learning Techniques
- Ensemble Methods: Random forests and boosting algorithms
- Model Evaluation: Metrics and cross-validation techniques
Deep Learning with TensorFlow and Keras
- Neural Networks: Building and training neural networks
- Advanced Architectures: Convolutional and recurrent neural networks
Natural Language Processing (NLP)
- Text Processing: Tokenization, stemming, and lemmatization
- Sentiment Analysis: Analyzing text sentiment and classification
Time Series Analysis
- Time Series Data: Handling and analyzing time series data
- Forecasting: Time series forecasting techniques
SQL for Data Science
- Database Management: SQL basics and advanced queries
- Data Integration: Integrating SQL with Python for data analysis
Big Data Technologies
- Introduction to Big Data: Concepts and applications
- Hadoop and Spark: Big data processing with Hadoop and Spark
Data Ethics and Governance
- Data Privacy: Understanding data privacy regulations
- Ethical Data Use: Ethical considerations in data science
Capstone Project
- Project Development: Develop a comprehensive data science project
- Presentation: Present your project findings and insights

Conclusion

The “Data Science Using Python Programming Course” at iMMEK Softech Academy is designed to provide you with a solid foundation in data science, equipped with the latest tools and techniques. With a focus on practical learning, expert instruction, and comprehensive career support, this course prepares you for a successful career in data science. Join iMMEK Softech Academy and take the first step towards becoming a proficient data scientist.

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Course Syllabus

Data Science Using Python Programming Course Syllabus at iMMEK Softech Academy

Introduction to Python Programming

Python Basics: Syntax, variables, and data types
Control Structures: Conditional statements and loops
Functions and Modules: Defining and using functions and modules

Python Data Structures

Lists and Tuples: Operations and applications
Dictionaries and Sets: Key-value pairs and set operations
Data Structure Manipulation: Advanced usage of lists, tuples, dictionaries, and sets

Working with Data in Python

File Handling: Reading from and writing to files
Data Input and Output: Handling various data formats (CSV, JSON, etc.)
Regular Expressions: Pattern matching and text processing

Numerical Computing with NumPy

NumPy Arrays: Creating and manipulating arrays
Mathematical Operations: Element-wise operations and broadcasting
Linear Algebra: Matrix operations and linear algebra functions

Data Manipulation with pandas

DataFrames: Creating and manipulating DataFrames
Data Cleaning: Handling missing data and data transformation
Merging and Joining: Combining multiple DataFrames

Data Visualization with Matplotlib

Basic Plotting: Line plots, bar charts, and scatter plots
Customizing Plots: Titles, labels, and legends
Advanced Visualization: Creating complex and interactive visualizations

Data Visualization with Seaborn

Seaborn Basics: Creating attractive statistical plots
Plot Types: Distribution plots, categorical plots, and regression plots
Customization: Enhancing and customizing Seaborn plots

Exploratory Data Analysis (EDA)

Descriptive Statistics: Measures of central tendency and dispersion
Data Exploration: Identifying patterns and outliers
Visualization Techniques: Heatmaps, pair plots, and correlation matrices

Introduction to Machine Learning

Machine Learning Basics: Supervised vs. unsupervised learning
Linear Regression: Simple and multiple linear regression
Logistic Regression: Binary classification problems

Supervised Learning Algorithms

Decision Trees: Understanding and implementing decision trees
Random Forests: Ensemble learning and random forests
Support Vector Machines (SVM): Classification with SVM

Unsupervised Learning Algorithms

Clustering: K-means and hierarchical clustering
Dimensionality Reduction: Principal Component Analysis (PCA)
Association Rules: Market basket analysis

Model Evaluation and Selection

Evaluation Metrics: Accuracy, precision, recall, and F1-score
Cross-Validation: K-fold cross-validation and hyperparameter tuning
Model Selection: Comparing and selecting the best model

Introduction to Deep Learning

Neural Networks: Basics of neural networks
TensorFlow and Keras: Building neural networks with TensorFlow and Keras
Training and Evaluating Models: Training, validation, and testing

Advanced Deep Learning Techniques

Convolutional Neural Networks (CNNs): Image classification and processing
Recurrent Neural Networks (RNNs): Sequence prediction and time series analysis
Transfer Learning: Pre-trained models and fine-tuning

Natural Language Processing (NLP)

Text Preprocessing: Tokenization, stemming, and lemmatization
Text Classification: Sentiment analysis and spam detection
Advanced NLP Techniques: Named entity recognition (NER) and topic modeling

Time Series Analysis

Time Series Data: Handling and visualizing time series data
Forecasting Techniques: ARIMA, exponential smoothing, and Prophet
Evaluating Time Series Models: Model performance metrics

SQL for Data Science

SQL Basics: Writing basic SQL queries
Advanced SQL: Joins, subqueries, and window functions
Integrating SQL with Python: Using SQLAlchemy and pandas

Big Data Technologies

Introduction to Big Data: Concepts and applications
Hadoop Ecosystem: HDFS, MapReduce, and YARN
Spark Basics: RDDs, DataFrames, and Spark SQL

Data Ethics and Governance

Data Privacy: Understanding data privacy laws and regulations
Ethical Data Use: Ethical considerations in data science projects
Data Governance: Best practices for data management and governance

Capstone Project

Project Development: Identifying a real-world problem and collecting data
Data Analysis and Modeling: Applying learned techniques to analyze data
Presentation: Presenting project findings and insights

This syllabus provides a comprehensive roadmap for mastering data science using Python, ensuring you gain both theoretical knowledge and practical skills to excel in the field.

Key Features: Data Science using Python Programming Course

Key Features of the “Data Science Using Python Programming Course” at iMMEK Softech Academy

Comprehensive Curriculum

In-Depth Content: The course covers a wide range of topics, including Python programming, data manipulation, data visualization, machine learning, and deep learning.
Updated Material: The curriculum is regularly updated to reflect the latest industry trends and technologies, ensuring that you stay ahead in the field.

Hands-On Learning

Real-World Projects: Engage in numerous hands-on projects that simulate real-world data science problems, allowing you to apply theoretical knowledge practically.
Interactive Coding Sessions: Participate in interactive coding sessions to solidify your understanding of Python and data science concepts.

Expert Instructors

Industry Professionals: Learn from experienced instructors who are industry professionals with extensive knowledge and expertise in data science and Python programming.
Personalized Guidance: Receive personalized attention and support from instructors to help you overcome any learning challenges.

Flexible Learning Options

Online and In-Person Classes: Choose between online and in-person classes to fit your schedule and learning preferences.
Flexible Timings: Attend classes at convenient times, including weekday and weekend batches, to accommodate working professionals and students.

State-of-the-Art Facilities

Modern Classrooms: Learn in a state-of-the-art learning environment equipped with the latest technology and tools.
Resource Access: Gain access to a wealth of resources, including online libraries, research papers, and software tools to enhance your learning experience.

Career Support

Job Placement Assistance: Benefit from comprehensive job placement services, including resume building, interview preparation, and job alerts to help you secure a position in the data science field.
Networking Opportunities: Connect with industry professionals, alumni, and peers through networking events and forums organized by iMMEK Softech Academy.

Industry-Relevant Certification

Recognized Certification: Earn a certification upon course completion that is recognized by industry leaders, enhancing your resume and opening doors to various career opportunities.
Portfolio Development: Build a strong portfolio of projects that showcase your skills to potential employers.

Strong Industry Connections

Partnerships and Collaborations: Benefit from iMMEK Softech Academy’s strong connections with leading companies and organizations in the industry.
Guest Lectures and Workshops: Gain insights from guest lectures and workshops conducted by industry leaders and experts.

Proven Track Record

Successful Alumni: Join a network of successful alumni who have gone on to work at top companies and organizations worldwide.
High Placement Rates: Enjoy high placement rates with many graduates securing positions in leading companies shortly after completing the course.

Practical Learning Environment

Interactive Learning: Engage in a practical, interactive learning environment that encourages participation and collaboration.
Real-Time Feedback: Receive real-time feedback on your assignments and projects to help you improve continuously.

Why Choose iMMEK Softech Academy?

Best Software Institute: Recognized as the best software institute for data science and Python programming, iMMEK Softech Academy stands out for its quality education, expert instructors, and comprehensive career support.
Commitment to Excellence: Dedicated to providing the highest quality education and training, ensuring that students are well-prepared for successful careers in data science.

Enroll in the “Data Science Using Python Programming Course” at iMMEK Softech Academy to gain the skills and knowledge needed to excel in the rapidly growing field of data science.

Placement Support at iMMEK Softech Academy for “Data Science Using Python Programming Course”

Comprehensive Career Services

At iMMEK Softech Academy, we understand that the ultimate goal of your education is to secure a rewarding career in data science. Our comprehensive placement support services are designed to help you achieve just that. Here’s how we support our students in their job search:

Personalized Career Counseling

Career Guidance: Receive personalized career guidance to help you identify your strengths, interests, and career goals.
Individual Mentorship: Benefit from one-on-one mentorship sessions with industry experts who provide valuable insights and advice tailored to your career aspirations.

Resume and Portfolio Building

Professional Resume Writing: Get assistance with crafting a professional resume that highlights your skills, projects, and achievements in data science.
Portfolio Development: Build a strong portfolio of real-world projects completed during the course, showcasing your practical experience to potential employers.

Interview Preparation

Mock Interviews: Participate in mock interview sessions conducted by experienced professionals to help you prepare for actual job interviews.
Interview Techniques: Learn effective interview techniques, including how to answer technical and behavioral questions confidently.

Job Placement Assistance

Job Alerts: Receive regular job alerts and notifications about new job openings in data science from our extensive network of industry partners.
Job Matching: Benefit from our job matching services, where we match your profile with suitable job opportunities based on your skills and preferences.

Networking Opportunities

Industry Connections: Leverage iMMEK Softech Academy’s strong connections with leading companies and organizations in the data science industry.
Networking Events: Attend networking events, workshops, and seminars to connect with industry professionals, alumni, and peers.

Alumni Network

Alumni Success Stories: Gain inspiration and guidance from the success stories of our alumni who have secured positions in top companies worldwide.
Mentorship Program: Participate in our alumni mentorship program, where successful graduates provide mentorship and career advice to current students.

Exclusive Job Fairs

Recruitment Drives: Take part in exclusive job fairs and recruitment drives organized by iMMEK Softech Academy, featuring top companies looking to hire data science professionals.
Employer Meet-and-Greets: Meet with potential employers, learn about their requirements, and present your skills and projects directly to hiring managers.

Continuous Learning and Development

Skill Enhancement Workshops: Attend workshops and training sessions to continuously enhance your skills and stay updated with the latest trends and technologies in data science.
Certifications: Earn industry-recognized certifications upon course completion, adding value to your resume and making you a more attractive candidate to employers.

Dedicated Placement Cell

Support Team: Our dedicated placement cell is always available to assist you with any queries or support you need during your job search.
Follow-Up: We follow up with employers on your behalf to ensure a smooth hiring process and to gather feedback for continuous improvement.

Why Choose iMMEK Softech Academy for Placement Support?

Proven Track Record: iMMEK Softech Academy has a proven track record of high placement rates, with many graduates securing positions in leading companies shortly after completing the course.
Comprehensive Support: Our comprehensive placement support services ensure that you are well-prepared and confident to enter the job market and succeed in your data science career.
Strong Industry Ties: Benefit from our strong industry connections and partnerships, providing you with ample job opportunities and career growth prospects.

At iMMEK Softech Academy, we are committed to helping you achieve your career goals and secure a successful position in the field of data science. Enroll in our “Data Science Using Python Programming Course” and take the first step towards a rewarding career with the support of our dedicated placement services.

Curriculum

Amazon Web Services (AWS) Training in Chennai with Python Course Syllabus

Module 1: Introduction to Data Science

1. What is Data Science?

2. What is Machine Learning?

3. What is Deep Learning?

4. What is AI?

5. Data Analytics & it’s types

Module 2: Introduction to Python

1. What is Python?

2. Why Python?

3. Installing Python

4. Python IDEs

5. Jupyter Notebook Overview

Module 3: Python Basics

1. Python Basic Data types

2. Lists

3. Slicing

4. IF statements

5. Loops

6. Dictionaries

7. Tuples

8. Functions

9. Array

10. Selection by position & Labels

Module 4: Python Packages

1. Pandas

2. Numpy

3. Sci-kit Learn

4. Mat-plot library

Module 5: Importing data

1. Reading CSV files

2. Saving in Python data

3. Loading Python data objects

4. Writing data to csv file

Module 6: Manipulating Data

1. Selecting rows/observations

2. Rounding Number

3. Selecting columns/fields

4. Merging data

5. Data aggregation

6. Data munging techniques

Module 7: Statistics Basics

1. Central Tendency
1.1. Mean
1.2. Median
1.3. Mode
1.4. Skewness
1.5. Normal Distribution

2. Probability Basics
2.1. What does mean by probability?
2.2. Types of Probability
2.3. ODDS Ratio?

3. Standard Deviation
3.1. Data deviation & distribution
3.2. Variance

4. Bias variance Trade off
4.1. Underfitting
4.2. Overfitting

5. Distance metrics
5.1. Euclidean Distance
5.2. Manhattan Distance

6. Outlier analysis
6.1. What is an Outlier?
6.2. Inter Quartile Range
6.3. Box & whisker plot
6.4. Upper Whisker
6.5. Lower Whisker
6.6. Catter plot
6.7. Cook’s Distance

7. Missing Value treatments
7.1. What is a NA?
7.2. Central Imputation
7.3. KNN imputation
7.4. Domifications

8. Correlation
8.1. Pearson correlation
8.2. Positive & Negative correlation

9. Error Metrics
9.1. Classification
9.2. Confusion Matrix
9.3. Precision
9.4. Recall
9.5. Specificity
9.6. F1 Score

10. Regression
10.1. MSE
10.2. RMSE
10.3. MAPE

Module 8: Machine Learning

Module 10: Unsupervised Learning

1. K-Means

2. K-Means ++

3. Hierarchical Clustering

Module 11: Other Machine Learning algorithms

1. K – Nearest Neighbors

2. Naïve Bayes Classifier

3. Decision Tree – CART

4. Decision Tree – C50

5. Random Forest

Placement Support at iMMEK Softech Academy

We are associated with top organizations like HCL, Wipro, Dell, Accenture, Google, CTS, TCS, IBM etc. It make us capable to place our students in top MNCs across the globe
We have separate student’s portals for placement, here you will get all the interview schedules and we notify you through Emails.
After completion of 70% Data Science with Python Training course content, we will arrange the interview calls to students & prepare them to F2F interaction
Data Science with Python Trainers assist students in developing their resume matching the current industry needs
We have a dedicated Placement support team wing that assist students in securing placement according to their requirements
We will schedule Mock Exams and Mock Interviews to find out the GAP in Candidate Knowledge

Job Salary for Data Science using Python Programming in India

Job Salaries for Freshers and Experienced Professionals in India

Freshers

For fresh graduates entering the field of data science, the starting salaries can be quite attractive. The average salary for a fresher in data science typically ranges from:

₹4,00,000 to ₹8,00,000 per annum.

Factors influencing this range include the reputation of the educational institution, the candidate’s skill set, project experience, and internship performance.

Experienced Professionals

Experienced professionals in data science can expect significantly higher salaries, depending on their expertise, years of experience, and the specific role. The average salary range for experienced data scientists in India is:

₹8,00,000 to ₹20,00,000 per annum for mid-level positions.
₹20,00,000 to ₹50,00,000 per annum for senior roles and data science managers.

Top Companies Hiring Data Scientists in India

Google India

Package: ₹18,00,000 to ₹60,00,000 per annum
Role: Data Scientist, Machine Learning Engineer, Data Analyst

Amazon India

Package: ₹15,00,000 to ₹50,00,000 per annum
Role: Data Scientist, Business Intelligence Engineer, Data Engineer

Microsoft India

Package: ₹16,00,000 to ₹55,00,000 per annum
Role: Data Scientist, Data and Applied Scientist, Data Analyst

Tata Consultancy Services (TCS)

Package: ₹6,00,000 to ₹30,00,000 per annum
Role: Data Scientist, Analytics Consultant, Machine Learning Engineer

Infosys

Package: ₹5,50,000 to ₹28,00,000 per annum
Role: Data Scientist, Data Analyst, AI Specialist

Accenture

Package: ₹7,00,000 to ₹35,00,000 per annum
Role: Data Scientist, Analytics Consultant, Data Engineer

IBM India

Package: ₹8,00,000 to ₹40,00,000 per annum
Role: Data Scientist, AI Engineer, Data Analyst

Cognizant

Package: ₹6,00,000 to ₹30,00,000 per annum
Role: Data Scientist, Analytics Specialist, Machine Learning Engineer

Wipro

Package: ₹5,50,000 to ₹25,00,000 per annum
Role: Data Scientist, Data Engineer, Analytics Consultant

Capgemini

Package: ₹7,00,000 to ₹32,00,000 per annum
Role: Data Scientist, Data Analyst, AI Specialist

Salary Determinants

Several factors influence the salary of data scientists, including:

Educational Background: Graduates from premier institutions such as IITs, IIMs, and reputed universities often command higher starting salaries.
Skill Set: Proficiency in programming languages (Python, R), machine learning algorithms, data visualization tools, and big data technologies.
Experience Level: Previous work experience, internships, and relevant project work.
Industry and Company: Salaries can vary significantly depending on the industry (tech, finance, healthcare) and the size and reputation of the company.
Location: Salaries in metropolitan areas like Bangalore, Mumbai, and Delhi tend to be higher due to the cost of living and demand for talent.

Conclusion

The field of data science offers lucrative career opportunities with competitive salaries for both freshers and experienced professionals. Top companies in India are actively hiring skilled data scientists and providing attractive compensation packages. By enrolling in the “Data Science Using Python Programming Course” at iMMEK Softech Academy, you can acquire the necessary skills and knowledge to tap into these opportunities and advance your career in data science.

We are associated with top organizations like HCL, Wipro, Dell, Accenture, Google, CTS, TCS, IBM etc. It make us capable to place our students in top MNCs across the globe
We have separate student’s portals for placement, here you will get all the interview schedules and we notify you through Emails.
After completion of 70% Data Science with Python Training course content, we will arrange the interview calls to students & prepare them to F2F interaction
Data Science with Python Trainers assist students in developing their resume matching the current industry needs
We have a dedicated Placement support team wing that assist students in securing placement according to their requirements
We will schedule Mock Exams and Mock Interviews to find out the GAP in Candidate Knowledge

Student Reviews for Data Science using Python Programming Course

Reviews for the “Data Science Using Python Programming Course” at iMMEK Softech Academy

Anbu Selvan
- “The course content is very comprehensive and up-to-date. The hands-on projects really helped me understand the concepts better. Highly recommend iMMEK Softech Academy!”
Priya Dharshini
- “Excellent course with experienced instructors. The placement support provided by iMMEK was instrumental in securing my first job as a data scientist.”
Rajesh Kumar
- “I was impressed by the depth of the curriculum and the quality of the teaching. The practical approach and real-world projects made a huge difference.”
Meenakshi Sundaram
- “The course structure is well-designed, and the instructors are very supportive. The career guidance and interview preparation were invaluable.”
Karthik Venkatesh
- “iMMEK Softech Academy’s data science course exceeded my expectations. The learning environment is conducive, and the resources provided are top-notch.”
Radhika Murali
- “The blend of theory and practice in this course is perfect. I gained a lot of confidence in my data science skills thanks to the thorough training.”
Siva Subramanian
- “The placement support at iMMEK is fantastic. They helped me with resume building, mock interviews, and job applications. I landed a job within a month of completing the course.”
Lakshmi Narayanan
- “The instructors are very knowledgeable and always willing to help. The projects we worked on were very relevant to the industry, which gave me a lot of confidence.”
Bhavani Sankar
- “Great course with a well-rounded curriculum. The flexibility of online classes allowed me to balance my work and studies effectively.”
Gowtham Raju
- “The data science course at iMMEK Softech Academy is well worth the investment. The practical assignments and projects helped me build a strong portfolio.”
Anitha Devi
- “I appreciated the detailed explanations and the practical applications of the concepts. The instructors were always ready to clarify doubts and provide additional support.”
Naveen Chandran
- “The learning experience was exceptional. The course content was relevant, and the instructors were very approachable and knowledgeable.”
Suganya Selvam
- “I found the course to be very engaging and informative. The placement support team was very proactive in helping me secure a job in a reputed company.”
Vikram Adithya
- “The course offered a perfect blend of theoretical knowledge and practical skills. The projects were challenging and rewarding, providing real-world experience.”
Mohana Priya
- “iMMEK Softech Academy’s data science course helped me transition to a new career. The instructors were supportive, and the curriculum was very relevant to the industry needs.”

These reviews reflect the positive experiences of students who have benefited from the “Data Science Using Python Programming Course” at iMMEK Softech Academy, highlighting the quality of education, practical training, and excellent placement support provided by the institute.

Velachery Reviews
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Velachery Reviews

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Frequently Asked Questions (FAQ) for the "Data Science Using Python Programming Course" at iMMEK Softech Academy

1. What is the duration of the "Data Science Using R Programming Course"?

The course duration is 6 months, including both theoretical and practical sessions.

2. Do I need any prior programming knowledge to enroll in this course?

Basic programming knowledge is recommended, but not mandatory. The course starts with the fundamentals of R programming.

3. What are the class timings?

We offer flexible class timings, including weekday and weekend batches to accommodate different schedules.

4. Is this course available online?

Yes, the course is available both online and in-person. You can choose the mode of learning that suits you best.

5. What is the fee structure for the course?

Please visit our website or contact our admissions office for detailed information on the fee structure and payment plans.

6. What topics are covered in this course?

The course covers a wide range of topics including R programming, data manipulation, data visualization, statistical analysis, machine learning, and more.

7. Are there any hands-on projects included in the course?

Yes, the course includes multiple hands-on projects and real-world case studies to apply the concepts learned.

8. Will I receive a certificate upon completion of the course?

Yes, you will receive a certificate of completion from iMMEK Softech Academy, recognized in the industry.

9. Is there any exam or assessment during the course?

Yes, there are periodic assessments, quizzes, and a final project that must be completed to earn the certificate.

10. Can I access course materials after the course ends?

Yes, you will have lifetime access to the course materials and recorded sessions.

11. Who are the instructors for this course?

The instructors are industry experts with extensive experience in data science and R programming.

12. Can I get one-on-one support from instructors?

Yes, our instructors are available for one-on-one sessions to provide personalized guidance and support.

13. What if I miss a class?

All classes are recorded, and you can access the recordings at any time to catch up on missed sessions

14. Is there any community or forum for students?

Yes, we have an active community forum where students can interact, ask questions, and collaborate on projects.

15. How can I contact the support team?

You can contact our support team via email, phone, or the online chat option available on our website.

16. Does the academy provide job placement assistance?

Yes, we offer comprehensive job placement assistance, including resume building, mock interviews, and job alerts.

17. What kind of companies hire graduates from this course?

Graduates have been hired by leading companies such as Google, Amazon, Microsoft, TCS, Infosys, and more.

18. What is the average salary for graduates of this course?

Freshers can expect an average salary of ₹4,00,000 to ₹8,00,000 per annum, while experienced professionals can earn significantly higher.

19. Are there any networking opportunities provided?

Yes, we organize industry events, webinars, and networking sessions with professionals and alumni.

20. Can I get career advice after completing the course?

Yes, our career services team offers ongoing support even after you have completed the course.

21. How do I enroll in the course?

You can enroll online through our website or visit our admissions office for assistance.

22. What are the payment options available?

We offer multiple payment options, including credit/debit cards, bank transfers, and installment plans.

23. Is there any scholarship or financial aid available?

Yes, we offer scholarships and financial aid to deserving candidates. Please contact our admissions office for more details.

24. Can I get a refund if I decide to drop out of the course?

Our refund policy is outlined on our website. Please review it or contact our support team for specific details.

25. What documents are required for enrollment?

You will need to submit a copy of your ID proof, educational certificates, and a recent passport-sized photograph.

These FAQs address the most common questions and concerns prospective students might have about the “Data Science Using R Programming Course” at iMMEK Softech Academy. If you have any additional questions, please feel free to reach out to us.

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Trainers Profile

Microsoft Azure Trainers are

Our MicroSoft Azure Training in Chennai. Trainers are certified professionals with 7+ years of experience in their respective domain as well as they are currently working with Top MNCs.
As all Trainers are MicroSoft Azure domain working professionals so they are having many live projects, trainers will use these projects during training sessions.
All our Trainers are working with companies such as Cognizant, Dell, Infosys, IBM, L&T InfoTech, TCS, HCL Technologies, etc.
Trainers are also help candidates to get placed in their respective company by Employee Referral / Internal Hiring process.
Our trainers are industry-experts and subject specialists who have mastered on running applications providing Best MicroSoft Azure training to the students.
We have received various prestigious awards for MicroSoft Azure Training in Chennai from recognized IT organizations.

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We are a unique Authorized Oracle Partner, Authorized Microsoft Azure Partner, Authorized Pearson Vue Exam Center, Authorized PSI Exam Center, Authorized Partner Of AWS & National Institute of Education (NIE) Singapore.
Microsoft Azure Training in Chennai is designed according to the current IT industry
The Microsoft Azure Training in Chennai is scheduled on weekdays, weekends and online Training . In addition, students can choose a customized schedule according to requirements
ACTE has got a collaboration 500+ MNCs and MLCs from the industry, that helps the trainees during their Microsoft Azure.
Our team of instructors are industry experts with more than ten years of training experience.
Mentors train Microsoft Azure Training in Chennai not only to assist students in implementing live projects, but also to hold a preparatory session for the interview along with community outreach.
The ultra-modern I.T laboratory is equipped with the latest infrastructure. Our laboratory is open 365 days a year. Students, at their discretion, may use the lab to complete projects and practice technical tasks
Our classrooms are equipped with a state-of-the-art I.T infrastructure, such as projectors, racks, Wi-Fi
We offer our students a room with a glass door and a discussion area (conference room) to enhance their learning and learning skills
We also organize valuable seminars on personal development and presentation skills
Our educational material includes ACTE’s student portal access to get the updated course materials, books and copies of didactic material in the form of PDF files, sample documents, Training videos, technical interviews and projects.
Students attending the Microsoft Azure Training in Chennai may also be located near hostels for their convenience
We help students, at no cost, study, teaching materials, copies of PDF files, video training, sample questions for appropriate certification and interview questions, and lab guides that are available on our site for quick access and also life time access of student portal for course materials in all format
Practical oriented domain specifically training is provided, to suit the needs of the industry Being a corporate training institute, at ACTE, training is provided at its corporate facility having state-of-the-art infrastructure
Trainees at ACTE are provided with unlimited interview calls, untill the time they are placed.
Add on training modules cover soft skills, communication skills, interview based training etc., to ensure the overall development of the trainees.
Our trainers pay you individual attention. To improve students' knowledge of complex technical concepts are passed on through simple trainingWe also Provide Internship for fresher’s with certification. Our certificates are recognized worldwide after the course ends
We accept Master and Visa cards (debit and credit) as well as cash, checks and internet access in payment mode

Student Interested

CLOUD COMPUTING Q/A

Our Somehow important lesson questions are here :

What is R, and why is it used in data science?

R is a programming language and software environment used for statistical analysis, data visualization, and predictive modeling. It’s widely used in data science due to its extensive library of statistical and graphical techniques, including linear and nonlinear modeling, classical statistical tests, time-series analysis, classification, and clustering.

Explain the difference between R and Python in data science.

Both R and Python are popular programming languages in data science, but they have some differences. R is specifically designed for statistical analysis and visualization and is favored for dedicated statistical computing. Python, on the other hand, is a general-purpose language that is versatile and can be used for a wider range of applications beyond data science, such as web development and software engineering. Python is known for its simplicity and readability, making it a good choice for beginners, while R has a steeper learning curve but provides advanced statistical capabilities.

How do you import data into R?

Data can be imported into R using various functions, depending on the format of the data. For example, read.csv() for CSV files, read.table() for tabular data, and readRDS() for RDS files. Additionally, packages like readxl can be used for Excel files, and jsonlite for JSON files.

Explain the use of the apply family of functions in R.

The apply family of functions in R, including apply(), lapply(), sapply(), vapply(), and tapply(), are used for performing operations on data structures in an efficient and concise manner. apply() is used for applying functions over the margins of an array or matrix. lapply() and sapply() are used for list objects, with sapply() simplifying the output. vapply() is similar to sapply(), but with a predefined type of return value, making it safer and faster. tapply() applies a function over subsets of a vector.

Describe what ggplot2 in R is used for.

ggplot2 is a plotting system for R based on the grammar of graphics. It provides a powerful framework for creating complex and aesthetically pleasing visualizations in a coherent and consistent manner. It’s widely used for exploratory data analysis and to visualize statistical models.

How do you handle missing values in R?

Missing values in R can be handled in several ways, including using na.omit() to remove rows with NA values, using na.exclude() to exclude NAs in model fitting, or using functions like impute() from the impute package to replace missing values with statistical imputations such as mean, median, or mode.

What is the significance of the Tidyverse in R?

The Tidyverse is a collection of R packages designed for data science that share an underlying design philosophy, grammar, and data structures. It includes packages like ggplot2 for visualization, dplyr for data manipulation, tidyr for tidying data, and readr for reading data. The Tidyverse makes data analysis in R easier, more intuitive, and more consistent.

How can you create a linear model in R?

A linear model in R can be created using the lm() function. For example, model <- lm(y ~ x, data = dataset) creates a linear model predicting y from x using the data in dataset. The summary of the model can be obtained using summary(model).

What are factors in R, and how do they differ from continuous variables?

Factors in R are used to represent categorical data and are stored as integers. Each integer has a corresponding label. Factors are useful in statistical modeling as they define the categorical nature of the data. They differ from continuous variables, which represent numeric data that can assume an infinite number of values within a range.

What are R packages, and can you name a few commonly used ones in data science?

R packages are collections of R functions, data, and compiled code in a well-defined format. They extend the capability of R by adding new functions. Commonly used R packages in data science include dplyr for data manipulation, ggplot2 for data visualization, caret for machine learning, shiny for interactive web apps, and tidyr for data tidying.

Explain the concept of data frames in R.

Data frames are key data structures in R that represent datasets in a tabular form, similar to a spreadsheet. Data frames consist of rows and columns, where each column can be of a different type (numeric, character, factor, etc.), and each row represents an observation.

How do you subset data in R?

Subsetting data in R can be done using the square brackets [ ], the $ operator for specific columns, or using functions like subset(). For example, data[rows, columns] allows subsetting by row and column numbers or names, and subset(data, condition) subsets rows based on a condition.

Describe the difference between rbind() and cbind() functions in R.

rbind() (row bind) function combines data frames or matrices by rows, whereas cbind() (column bind) function combines them by columns. They are used to merge data structures by adding rows or columns, respectively.

How do you deal with duplicate values in R?

Duplicate values in R can be identified and removed using the duplicated() function, which returns a logical vector indicating which rows are duplicates. The unique() function can be used to extract a data frame without duplicates.

Explain the difference between list() and c() functions in R.

The list() function in R is used to create lists, which can contain objects of different types and lengths, including other lists. The c() function combines its arguments to form a vector, but it only holds objects of the same type, coercing them if necessary.

What is the purpose of the set.seed() function in R?

set.seed() is used to specify the starting point for generating a sequence of random numbers in R. It ensures the reproducibility of results that involve random number generation.

How can you merge two data frames in R?

Two data frames can be merged using the merge() function. For example, merge(df1, df2, by = "key") merges df1 and df2 on the column named “key”.

What is the significance of the %>% operator in R?

The %>% operator, also known as the pipe operator from the magrittr package and heavily used in Tidyverse, allows for the chaining of functions in a more readable manner. It passes the result of the left-hand side expression as the first argument to the function on the right-hand side.

Explain how you can perform type conversion in R.

Type conversion in R can be performed using functions like as.numeric(), as.character(), as.factor(), etc. These functions convert objects from one class to another.

What is the use of the str() function in R?

The str() function provides a compact, human-readable summary of the structure of an R object. It’s useful for quickly understanding the type, length, and content of the object, making it an essential tool for data exploration.

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