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Course Highlights and Why Data Science Course in Chennai at FITA Academy?
The course equips both theoretical conceptions and practical implementations. The Data Science Course in Chennai by FITA Academy deals with various related subjects. Elaborate courseware covering various aspects such as Python/R with Data Science. Students can build models using Data Science algorithms, analyse datasets from real-world environments, and create interactive visualisations to practice what they learn. The Data Science Training in Chennai has flexible batch timings that allow us to provide classes to students on weekends, weekdays, and fast-track sessions. FITA Academy has over 3000 companies who are heavily in demand for Data Scientists, Data Analysts, etc. We are partnering with such organizations to provide placement services. 100% Placement support is offered by FITA Academy for all the students after completion of training. Upcoming Batches
- 28-12-2024
- Weekend
- Saturday (Saturday - Sunday)
- 30-12-2024
- Weekdays
- Monday (Monday - Friday)
- 02-01-2025
- Weekdays
- Thursday (Monday - Friday)
- 04-01-2025
- Weekend
- Saturday (Saturday - Sunday)
Classroom Training
- Get trained by Industry Experts via Classroom Training at any of the FITA Academy branches near you
- Why Wait? Jump Start your Career by taking Data Science Course in Chennai!
Instructor-Led Live Online Training
- Take-up Instructor-led Live Online Training. Get the Recorded Videos of each session.
- Travelling is a Constraint? Jump Start your Career by taking the Data Science Training Online!
Data Science Course Objectives
- Get to know the basics of Data Science by introducing concepts like Data Science Life Cycle.
- Students are introduced to Python or R programming, its versions, and an in-depth study of the programming languages. They can choose between either of the programming languages.
- Read through what is Fundamental Statistics, the application of Statistical Analysis, and distinguish between Inferential and Descriptive Statistics.
- Data Science Models and Algorithms, for instance, Predictive Models, Predictive Analyses, linear regression, and Polynomial Regression.
- Being acquaintance with Supervised and Unsupervised Learning Algorithms, Hypothesis Testing and Reinforcement Learning Algorithms.
Data Science Course Syllabus
Introduction to Data Science
- Understanding Data Science
- The Data Science Life Cycle
- Understanding Artificial Intelligence (AI)
- Overview of Implementation of Artificial Intelligence
- Machine Learning
- Deep Learning
- Artificial Neural Networks (ANN)
- Natural Language Processing (NLP)
- How R connected to Machine Learning
- R - as a tool for Machine Learning Implementation
Data Science with Python: Introduction to Python
- What is Python and history of Python
- Python-2 and Python-3 differences
- Install Python and Environment Setup
- Python Identifiers, Keywords and Indentation
- Comments and document interlude in Python
- Command line arguments and Getting User Input
- Python Basic Data Types and Variables
List, Ranges & Tuples in Python
- Understanding Lists in Python
- Understanding Iterators
- Generators, Comprehensions and Lambda Expressions
- Understanding and using Ranges
Python Dictionaries and Sets
- Introduction to the section
- Python Dictionaries and More on Dictionaries
- Sets and Python Sets Examples
Input and Output in Python
- Reading and writing text files
- Appending to Files
- Writing Binary Files Manually and using Pickle Module
Python functions
- Python user defined functions
- Python packages functions
- The anonymous Functions
- Loops and statement in Python
- Python Modules & Packages
Python Exceptions Handling
- What is Exception?
- Handling an exception
- try….except…else
- try-finally clause
- Argument of an Exception
- Python Standard Exceptions
- Raising an exceptions
- User-Defined Exceptions
Python Regular Expressions
- What are regular expressions?
- The match Function and the Search Function
- Matching vs Searching
- Search and Replace
- Extended Regular Expressions and Wildcard
Useful additions
- Collections – named tuples, default dicts
- Debugging and breakpoints, Using IDEs
Data Manipulation using Python
- Understanding different types of Data
- Understanding Data Extraction
- Managing Raw and Processed Data
- Wrangling Data using Python
- Using Mean, Median and Mode
- Variation and Standard Deviation
- Probability Density and Mass Functions
- Understanding Conditional Probability
- Exploratory Data Analysis (EDA)
- Working with Numpy, Scipy and Pandas
Understanding Machine Learning Models
- Understand what is a Machine Learning Model
- Various Machine Learning Models
- Choosing the Right Model
- Training and Evaluating the Model
- Improving the Performance of the Model
More on Models
- Understanding Predictive Model
- Working with Linear Regression
- Working with Polynomial Regression
- Understanding Multi Level Models
- Selecting the Right Model or Model Selection
- Need for selecting the Right Model
- Understanding Algorithm Boosting
- Various Types of Algorithm Boosting
- Understanding Adaptive Boosting
Understanding Machine Learning Algorithms
- Understanding the Machine Learning Algorithms
- Importance of Algorithms in Machine Learning
- Exploring different types of Machine Learning Algorithms
- Supervised Learning
- Unsupervised Learning
- Reinforcement Learning
Exploring Supervised Learning Algorithms
- Understanding the Supervised Learning Algorithm
- Understanding Classifications
- Working with different types of Classifications
- Learning and Implementing Classifications
- Logistic Regression
- Naïve Bayes Classifier
- Nearest Neighbour
- Support Vector Machines (SVM)
- Decision Trees
- Boosted Trees
- Random Forest
- Time Series Analysis (TSA)
- Understanding Time Series Analysis
- Advantages of using TSA
- Understanding various components of TSA
- AR and MA Models
- Understanding Stationarity
- Implementing Forecasting using TSA
Exploring Un-Supervised Learning Algorithms
- Understanding Unsupervised Learning
- Understanding Clustering and its uses
- Exploring K-means
- What is K-means Clustering
- How K-means Clustering Algorithm Works
- Implementing K-means Clustering
- Exploring Hierarchical Clustering
- Understanding Hierarchical Clustering
- Implementing Hierarchical Clustering
- Understanding Dimensionality Reduction
- Importance of Dimensions
- Purpose and advantages of Dimensionality Reduction
- Understanding Principal Component Analysis (PCA)
- Understanding Linear Discriminant Analysis (LDA)
Understanding Hypothesis Testing
- What is Hypothesis Testing in Machine Learning
- Advantages of using Hypothesis Testing
- Basics of Hypothesis
- Normalization
- Standard Normalization
- Parameters of Hypothesis Testing
- Null Hypothesis
- Alternative Hypothesis
- The P-Value
- Types of Tests
- T Test
- Z Test
- ANOVA Test
- Chi-Square Test
Overview Reinforcement Learning Algorithm
- Understanding Reinforcement Learning Algorithm
- Advantages of Reinforcement Learning Algorithm
- Components of Reinforcement Learning Algorithm
- Exploration Vs Exploitation tradeoff
Data Science with R: Introduction to R Programming
- What is R?
- History and Features of R
- Introduction to R Studio
- Installing R and Environment Setup
- Command Prompt
- Understanding R programming Syntax
- Understanding R Script Files
R Programming Basics
- Data types in R
- Creating and Managing Variables
- Understanding Operators
- Assignment Operators
- Arithmetic Operators
- Relational and Logical Operators
- Other Operators
- Understanding and using Decision Making Statements
- The IF Statement
- The IF…ELSE statement
- Switch Statement
- Understanding Loops and Loop Control
- Repeat Loop
- While Loop
- For Loop
- Controlling Loops with Break and Next Statements
More on Data Types
- Understanding the Vector Data type
- Introduction to Vector Data type
- Types of Vectors
- Creating Vectors and Vectors with Multiple Elements
- Accessing Vector Elements
- Understanding Arrays in R
- Introduction to Arrays in R
- Creating Arrays
- Naming the Array Rows and Columns
- Accessing and manipulating Array Elements
- Understanding the Matrices in R
- Introduction to Matrices in R
- Creating Matrices
- Accessing Elements of Matrices
- Performing various computations using Matrices
- Understanding the List in R
- Understanding and Creating List
- Naming the Elements of a List
- Accessing the List Elements
- Merging different Lists
- Manipulating the List Elements
- Converting Lists to Vectors
- Understanding and Working with Factors
- Creating Factors
- Data frame and Factors
- Generating Factor Levels
- Changing the Order of Levels
- Understanding Data Frames
- Creating Data Frames
- Matrix Vs Data Frames
- Sub setting data from a Data Frame
- Manipulating Data from a Data Frame
- Joining Columns and Rows in a Data Frame
- Merging Data Frames
- Converting Data Types using Various Functions
- Checking the Data Type using Various Functions
Functions in R
- Understanding Functions in R
- Definition of a Function and its Components
- Understanding Built in Functions
- Character/String Functions
- Numerical and Statistical Functions
- Date and Time Functions
- Understanding User Defined Functions (UDF)
- Creating a User Defined Function
- Calling a Function
- Understanding Lazy Evaluation of Functions
Working with External Data
- Understanding External Data
- Understanding R Data Interfaces
- Working with Text Files
- Working with CSV Files
- Understanding Verify and Load for Excel Files
- Using WriteBin() and ReadBin() to manipulate Binary Files
- Understanding the RMySQL Package to Connect and Manage MySQL Databases
Data Visualization with R
- What is Data Visualization
- Understanding R Libraries for Charts and Graphs
- Using Charts and Graphs for Data Visualizations
- Exploring Various Chart and Graph Types
- Pie Charts and Bar Charts
- Box Plots and Scatter Plots
- Histograms and Line Graphs
Exploring Statistical Computations using R
- Understanding the Basics of Statistical Analysis
- Uses and Advantages of Statistical Analysis
- Understanding and using Mean, Median and Mode
- Understanding and using Linear, Multiple and Logical Regressions
- Generating Normal and Binomial Distributions
- Understanding Inferential Statistics
- Understanding Descriptive Statistics and Measure of Central Tendency
Packages in R
- Understanding Packages
- Installing and Loading Packages
- Managing Packages
Understanding Machine Learning Models
- Understand what is a Machine Learning Model
- Various Machine Learning Models
- Choosing the Right Model
- Training and Evaluating the Model
- Improving the Performance of the Model
More on Models
- Understanding Predictive Model
- Working with Linear Regression
- Working with Polynomial Regression
- Understanding Multi Level Models
- Selecting the Right Model or Model Selection
- Need for selecting the Right Model
- Understanding Algorithm Boosting
- Various Types of Algorithm Boosting
- Understanding Adaptive Boosting
Understanding Machine Learning Algorithms
- Understanding the Machine Learning Algorithms
- Importance of Algorithms in Machine Learning
- Exploring different types of Machine Learning Algorithms
- Supervised Learning
- Unsupervised Learning
- Reinforcement Learning
Exploring Supervised Learning Algorithms
- Understanding the Supervised Learning Algorithm
- Understanding Classifications
- Working with different types of Classifications
- Learning and Implementing Classifications
- Logistic Regression
- Naïve Bayes Classifier
- Nearest Neighbor
- Support Vector Machines (SVM)
- Decision Trees
- Boosted Trees
- Random Forest
- Time Series Analysis (TSA)
- Understanding Time Series Analysis
- Advantages of using TSA
- Understanding various components of TSA
- AR and MA Models
- Understanding Stationarity
- Implementing Forecasting using TSA
Exploring Un-Supervised Learning Algorithms
- Understanding Unsupervised Learning
- Understanding Clustering and its uses
- Exploring K-means
- What is K-means Clustering
- How K-means Clustering Algorithm Works
- Implementing K-means Clustering
- Exploring Hierarchical Clustering
- Understanding Hierarchical Clustering
- Implementing Hierarchical Clustering
- Understanding Dimensionality Reduction
- Importance of Dimensions
- Purpose and advantages of Dimensionality Reduction
- Understanding Principal Component Analysis (PCA)
- Understanding Linear Discriminant Analysis (LDA)
Understanding Hypothesis Testing
- What is Hypothesis Testing in Machine Learning
- Advantages of using Hypothesis Testing
- Basics of Hypothesis
- Normalization
- Standard Normalization
- Parameters of Hypothesis Testing
- Null Hypothesis
- Alternative Hypothesis
- The P-Value
- Types of Tests
- T Test
- Z Test
- ANOVA Test
- Chi-Square Test
Overview Reinforcement Learning Algorithm
- Understanding Reinforcement Learning Algorithm
- Advantages of Reinforcement Learning Algorithm
- Components of Reinforcement Learning Algorithm
- Exploration Vs Exploitation tradeoff
Data Science Course Trainer Profile
- FITA Academy trainers possess over a decade of experience in different domains of Data Science like Data analysis, Data analytics, data engineering, etc.
- They are certified professionals with sufficient training experience in tutoring as well.
- To gain industry experience, the FITA Academy’s Data Science Training Institute in Chennai trainers provide detailed hands-on training and have the students work on real-time projects during training.
- The trainers train students on the latest algorithms, tools, and methods in data science.
- Regular recap sessions ensure students keep track of what they are learning.
- At FITA Academy, trainers guide students through the necessary interview tips and provide support in building a successful resume as part of their training.
- Trainers teach students how to improve their competencies in Data Science to gain competitive employment.
Learn at FITA Academy & Get Your
Dream IT Job in 60 Days
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Student Success Story of Data Science Course in Chennai
Anitha is a mother of a two year old girl. She graduated 5 years ago and worked for a year before quitting following marriage. She was thinking of resuming her career after financial responsibilities started to increase after the birth of her child. Her job search efforts were futile due to her long career break and lack of update in skillsets. That’s when she approached FITA Academy, after being referred by one of her cousins.
She chose the Best Data Science Courses in Chennai, leveraging her experience with spreadsheets and databases. To balance her family commitments, especially caring for her child, she opted for an online course. Managing both family and education was challenging, but her determination never wavered.
Despite these hurdles, she excelled in her studies, attending sessions regularly and completing the capstone projects with outstanding performance. Her dedication and resilience showcased her passion for learning, and her drive to achieve her career goals. This journey is an inspiring example of overcoming obstacles to pursue personal and professional growth.
With our placement cell, she obtained training for placements and interviews. With her updated knowledge, she aced the interviews quickly this time around. She got placed in 3 companies namely Team Everest, Accenture and Foyer Technologies. She opted for Accenture, where she got the offer as a Data Engineer for a salary of 6 LPA. FITA Academy helped Anita to start her second innings of her career as a model.
Features of Data Science Course in Chennai at FITA Academy
Real-Time Experts as Trainers
At FITA Academy, you will learn from industry experts eager to share their knowledge with learners. You will also get personally mentored by the Experts.
LIVE Project
Get the opportunity to work on real-time projects that will provide you with deep experience. Showcase your project experience and increase your chances of getting hired!
Certification
FITA Academy offers certification. Also, get ready to clear global certifications. 72% of FITA Academy students appear for global certifications and 100% of them clear it.
Affordable Fees
At FITA Academy, the course fee is not only affordable, but you can also pay it in installments. Quality training at an affordable price is our motto.
Flexibility
At FITA Academy, you get the ultimate flexibility. Classroom or online training? Early morning or late evening? Weekday or weekend? Regular Pace or Fast Track? - Choose whatever suits you best.
Placement Support
Tied-up & signed MOUs with over 3000+ small & medium-sized companies to support you with opportunities to kick-start & advance your career.
Why Learn Data Science Course in Chennai at FITA Academy?
Live Capstone Projects
Real time Industry Experts as Trainers
Placement Support till you get your Dream Job offer!
Free Interview Clearing Workshops
Free Resume Preparation & Aptitude Workshops
Data Science Certification Training in Chennai
Upon the end of the Data Science Course that our institute provides, students are issued course completion certificates. The certificate recognises the candidate’s capacity to gain complete subject comprehension and master all essential tools and algorithms used by Data Science experts. This certification is on the part of the student that he or she is fit for the best job opportunities in multinational organisations. Employing a bright Personality might help a person gain a good impression on the interviewer and lead to a job offer. The Data Science Certification in Chennai has helped students gain insight into the primary services within this field.
This certification and a polished and confident personality enable students to make a positive impression during interviews, often leading to promising career prospects. The course focuses on technical expertise and nurturing essential soft skills, preparing students for success in the competitive job market. The Data Science Certification in Chennai has empowered students with deep insights into the key methodologies and practices of Data Science, equipping them to excel in various roles within this dynamic and growing field.
Besides the one provided by FITA Academy, there are several certifications available for Data Science which are internationally recognised. Data Science Course in Chennai helps students prepare for the below certifications. Some of them are,
- Google Professional Data Engineer Certification
- Microsoft Certified Azure Data Scientist Associate Certification
- Dell EMC Data Science Certification
- IBM Data Science Professional Certification
- SAS Certified Data Scientist
Have Queries? Talk to our Career Counselor for more Guidance on picking the
right Career for you!
Placement Session & Job Opportunities after completing Data Science Course in Chennai
Managing large amounts of data flowing into social media and e-commerce sites requires the expertise of data scientists. The majority of companies also consider data scientists to be the right path to embracing Artificial Intelligence. The technical skills from Data Science and Artificial Intelligence Courses in Chennai tool sets required by businesses are popular courses. The expected hike in these factors will bring the number of jobs in data science in the next year to 30% higher than the previous year. FITA Academy understands this very well we pay paramount importance to training students for doing internships and to get jobs through the Data Science Course in Chennai with placement. We also provide Corporate Training in Chennai with which you can get insights at your workplace.
Data Scientist Salary for Freshers from Rs. 6 to 8 lakhs annually for new graduates. With four to five years of experience and a strong skill set, professionals in the field can earn over Rs. 15 lakhs annually. Data science is a domain that provides excellent paid opportunities and its future looks bright for those who master the instruments for analysis and decision making. The Data Science Course in Chennai provide knowledge and practical experience to face competition in this data science field. At FITA Academy, we do practical projects and like-minded guidance to succeed in data science profession that you have dreamt of.
“Students are offered 100% placement training & Assistance at the end of the course.”
What are the job opportunities for course completion?
Completing a Data Science course in Chennai opens doors to abundant job opportunities. At FITA Academy, students are trained by experienced trainers with hands-on industry experience. The curriculum covers advanced programming languages like R, Python, and SQL, equipping students with essential skills for a thriving career in Data Science. All these competencies help you to acquire the right job in the subject area of your choice. It is possible to mention the following positions today as popular ones: Data Analyst, Machine Learning Engineer, Data Scientist, Business Analyst. Moreover, with professional coaching real skills applied knowledge.
Data Analyst: Data Analysts are very important in organizations because they identify business issues and use data to answer questions and provide corrective measures. This role typically fits best for junior positions in Data science, where individuals are trained on how to begin applying and making data-informed decisions. Some of the assignments incumbent on the tacticians include cleaning, analyzing, interpreting data and displaying these findings through visualizations that are closely aligned to strategic ones. Knowledgeable in programming languages such as Python helps the analyst deal with a large dataset, carry out data mining and result in an actionable report. Indeed, Data Analysts help contribute to a company’s growth in every aspect of its operations and decision-making processes since they convert raw data into usable and comprehensible information.
Data Scientist: Data scientists possess strong statistical skills and design Machine Learning strategies to perform predictive analytics and solve critical business challenges. They extract valuable insights from data using supervised and unsupervised learning methods in their Machine Learning models. By training mathematical models, they identify patterns and forecast business trends accurately. A Data Science Course in Chennai prepares the learner to face the real world after providing them with the skills needed to work through the data and develop perfect models. Managing data and learning the practical part of data science and business intelligence in their entirety and detail, learners acquire practical knowledge in data visualization, statistical analysis, and machine learning concepts needed to make important business decisions.
Data Engineer: Data Engineers support improving the delivery of the optimum system so that data scientists and analysts can do their work. A data engineer is responsible for the correct data and its preparation for storage and utilisation by its consumers for data analytics, among other uses. Their function will include maintaining that data is properly acquired, preserved, and disseminated for other purposes, such as data mining to the users. A strong technical knowledge base is essential for creating and integrating APIs (Application Program Interfaces) and maintaining the data infrastructure, critical skills emphasised in a Data Science Classes in Chennai.
Leading Companies with the Highest Number of Analytics Job Vacancies
- Amazon
- Accenture
- KPMG
- Deloitte
- Honeywell
- Wells Fargo
- Ernst and Young
- eClerk Assistance
- Hexaware Tech Solutions
- Dell Global
Student's Success Story of Data Science Course in Chennai
Preethi krishnan
It was a good experience to learn Data science. Here a practical oriented approach teaching was provided. The trainer was very friendly and taught me all the topics in detail.All the doubts were cleared immediately. The training infrastructure was very good. Many practical example were given.
Sushmita
FITA Academy is a good place to get Data Science Training under experts from the Data Science domain. The flexibly scheduled timing was more convenient for me to attend classes without any distractions. In the practical sessions, they offered training with hands-on projects which was more helpful for me to enhance my knowledge technically. Thanks to FITA Academy and the trainer.
Thenmozhi raj
I have done data science course here. Very friendly staff and wonderful atmosphere. Every session was perfect with the best explanation. Perfect place to learn this course.
Our Students Work at
Frequently Asked Question (FAQ) about Data Science Course in Chennai
- This FITA Academy Data Science Course is designed and trained by Data Science experts with 10+ years of experience as Data Analysts, Data Scientists, Data Engineer etc.
- A blend of hands-on practical sessions with real-world examples is provided.
- Affordable fees, keeping students and IT working professionals in mind.
- The course is convenient to undertake since it covers the normal working hours of a professional or student.
- The final training after the course is focused on placement training.
- We give Interview Tips for job interviews.
FITA Academy has tie-ups with more than 3,000 IT companies, most of which have existing or vacant positions for different positions related to data science. Besides, our highly active placement cell offers 100% placements to the students. The cell also contributes by training students in mock interviews and Data Science Interview Questions and Answers even after the course completion.
If you are interested in the accelerating your inquiries about the Data Science Course in Chennai eligibility or any Data Science course near me branches, dial our support number 93450 45466 or else you can just pop on to any of our branches in Chennai as soon as possible.
You can Enroll in any of our branches in Velachery, Anna Nagar, T Nagar, Tambaram, Pallikaranai, and Thoraipakkam OMR. In every FITA Academy branch in Chennai, the data science syllabus and learning methodology are uniformly standardized.
Our Data Science faculty members are industry experts who have extensive experience in the field handling real-life data and completing mega real-time projects in related areas like Big Data, AI, and Data Analytics in different Data Science Tutorial of the industry.
General Q & A about Data Science Course in Chennai
Where can I study a data science in the best place in Chennai?
Is data science costly?
Is there a demand for data science job?
What is Data Science?
Why is Data Science important?
Does data science need coding?
Which language is used for data science?
- Python
- SQL
- R
- Julia
- JavaScript
- Scala
- Java
- Go
Can I learn Data Science in 3 months?
Why and How Data Science is Considers as a Difficult Course?
Is it Possible to do Data Science If I am Weak in Math?
Want to be a Data Scientist?
To succeed as a data scientist, you should focus on the following:
- Programming languages like Python or R among others courtesy of the well established Department of Computer Science at the University of Warwick.
- Innovativeness and creativity added to it strategic knowledge in statistics and mathematics.
- Meta skills related to data manipulation and being able to extract insights from the data using SQL and Pandas.
- Awareness of machine learning and possibility to use appropriate algorithms and techniques.
Is data science a high paying career?
Is Future of Data science bright?
Does Google Have Data Scientist Position?
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