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Data Science Course in Chennai

Job-ready Data Science course in Chennai with placement assistance.
Master Python, ML, Deep Learning, Generative AI, NLP, Hadoop, Spark and popular data science tools through hands-on projects.
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The image illustrates mastering the foundations of Data Science with a diploma in Data Science.

Data Science Course: An Overview

Master data science with Aimore's Chennai Data Science Course, featuring interactive offline classes, real-world projects, and industry-recognized certifications. In today's tech world, data is gold, and data science expertise is paramount for career advancement.

What are the key skills covered in a Data Science Course? To equip you fully, our comprehensive curriculum covers the entire Data Science lifecycle. You'll learn essential foundations like Statistics, Probability, and programming with Python and R. We then delve into crucial processes such as Data Collection, Extraction, Cleansing, Exploratory Data Analysis (EDA), and Transformation. You'll master key techniques including Statistical Analysis, Feature Engineering, Regression Modeling, and Data Mining (both Supervised methods like Linear Regression and Unsupervised methods like Clustering and Dimension Reduction). We also cover Machine Learning algorithms, introduction to Deep Learning and Neural Networks, and Text Mining.

As Artificial Intelligence and ML advance, Data Science becomes more accurate. Aimore, the best software training institute in Chennai, offers this cutting-edge data science training, with placement assistance, to prepare you for the future. Our training focuses on practical skills using real-world scenarios and includes placement assistance, equipping you with the expertise and cross-functional abilities needed to excel.

Why Choose Us for Your Chennai Data Science Training?

Hybrid Learning
Experience a blend of online lectures, case studies, workshops, and practical sessions enriched with real-world examples for hands-on experience.
Feedback Sessions
Gain knowledge by asking questions and receiving feedback that can help you get in-depth insights about the subject matter.
Comprehensive Curriculum
Explore the nuances of Data Science and AI through an all-encompassing curriculum that covers it all.
Exemplary Training
Learn Machine Learning, R Programming, Artificial Intelligence, and Python along with our Data Science and AI course.
Assured Placement
Our Data Science & AI training program in Chennai comes with a 100% placement guarantee as soon as you finish the course.
Flexible Timings
Learn at your own pace with flexible timings that suit your needs and commitments.
Assured Certification
Gain a Data Science & AI certification solely based on your performance in the practical sessions and internal assessments.
Professional Guidance
Get trained by industry-leading professionals with in-depth knowledge of data science and AI.

Data Science Course Syllabus

Python
Statistics
Machine Learning
Deep Learning
NLP
Power BI
Module1:
Introduction to Python
Module2:
Accessing/Importing and Exporting Data using python modules
Module3:
Data Manipulation โ€“ cleansing โ€“ Munging using Python modules
  • Overview of Python- Starting with Python
  • Introduction to installation of Python
  • Introduction to Python Editors & IDE's (Canopy, pycharm, Jupyter, Rodeo, Ipython etcโ€ฆ)
  • Understand Jupyter notebook & Customize Settings
  • Concept of Modules/Libraries - Important packages (NumPy, SciPy, scikit-learn, Pandas, Matplotlib, etc)
  • Installing & loading Packages & Name Spaces
  • Data Types & Data objects/structures (strings, Tuples, Lists, Dictionaries)
  • List and Dictionary Comprehensions
  • Variable & Value Labels โ€“ Date & Time Values
  • Basic Operations - Mathematical - string - date
  • Reading and writing data
  • Control flow & conditional statements
  • Errors and exception handling
  • Importing Data from various sources (Csv, txt, excel, access etc.)
  • Database Input (Connecting to database)
  • Viewing Data objects - sub setting, methods
  • manipulating data
  • Combining data
  • Exporting Data to various formats
  • Important python modules: Pandas
  • Cleansing Data with Python
  • Data Manipulation steps(Sorting, filtering, duplicates, merging, appending, subsetting, derived variables, sampling, Data type conversions, renaming, formatting etc)
  • Data manipulation tools(Operators, Functions, Packages, control structures, Loops, arrays etc)
  • Python Built-in Functions (Text, numeric, date, utility functions)
  • Python User Defined Functions
  • Normalizing data
  • Formatting data
  • Important Python modules for data manipulation (Pandas, Numpy, math, string, datetime etc)
  • Basic Statistics - Measures of Central Tendencies and Variance
  • Inferential Statistics -Sampling - Concept of Hypothesis Testing
  • Exploratory data analysis
  • Descriptive statistics, Frequency Tables and summarization
  • Creating Graphs- Simple plotting/Bar/pie/line chart/histogram/ boxplot/ scatter etc)
  • Important Packages for Exploratory Analysis(NumPy Arrays, Matplotlib, Pandas and scipy.stats etc)
  • Important modules for statistical methods: Numpy, Scipy, Pandas
Module1:
Introduction to Machine Learning
Module2:
Implementing machine learning
Module3:
Supervised Learning Tasks and Algorithms
Module4:
Unsupervised Learning Tasks and Algorithms
  • Origin and the history of machine learning
  • Differences between AI and machine learning
  • Differences between data science, statistics, data mining and machine learning
  • Applications of machine learning
  • Limitations of machine learning
  • Machine learning is the future

Machine Learning Process

  • Collecting data
  • Pre-processing and preparing data
  • Exploring data
  • Choosing a model
  • Training the model
  • Evaluating the model
  • Improving the performance of model

Machine Learning Theories and Algorithms

  • Meaning of algorithm
  • Importance of algorithms in machine learning

Types of Machine Learning Algorithms

  • Supervised learning
  • Unsupervised learning
  • Semi-supervised learning
  • Reinforcement learning
Classification
  • Nearest neighbor (non-parametric /instance-based)
  • Decision trees (non-metric /symbolic)
  • Naive bayes theorem (parametric /probabilistic)
Numeric Prediction
  • Linear Regression
  • Multiple Regression
  • Logistic Regression
  • Time Series Forecasting
Pattern detection
  • Association rules (rule based learning)
  • Apriori Algorithm
Clustering
  • K Means Clustering
  • Hierarchical clustering
Black Box Method
  • Support Vector Machines(SVM)
Ensemble Methods
  • Random Forest
  • Bagging
  • Boosting
Data Preprocessing in Python
  • Standardization and Normalization
  • Missing value replacement
  • Resampling
  • Discretization
  • Feature Selection
  • Dimensionality Reduction
  • Neural Networks (Perceptron, MLP)
  • Activation Functions (ReLU, Sigmoid, Tanh)
  • Loss Functions (MSE, Cross-Entropy)
  • Optimization (Gradient Descent, Adam, RMSprop)
  • Backpropagation
  • Convolutional Neural Networks (CNNs)
  • Recurrent Neural Networks (RNNs)
  • Long Short-Term Memory (LSTM) & Gated Recurrent Unit (GRU)
  • Transformers (Self-Attention Mechanism)
Module1:
Fundamentals of NLP
Module2:
Text Representation Techniques
Module3:
Syntactic & Semantic Processing
Module4:
Classical NLP Techniques
  • Tokenization (Word & Sentence Tokenization)
  • Lemmatization & Stemming
  • Stopword Removal
  • Part-of-Speech (POS) Tagging
  • Named Entity Recognition (NER)
  • Regular Expressions for Text Processing
  • Bag of Words (BoW)
  • Term Frequency-Inverse Document Frequency (TF-IDF)
  • Word Embeddings (Word2Vec, GloVe, FastText)
  • Contextual Embeddings (ELMo, BERT, GPT)
  • Dependency Parsing
  • Constituency Parsing
  • Semantic Role Labeling (SRL)
  • Coreference Resolution
  • Text Classification (Naรฏve Bayes, SVM, Random Forest)
  • Sentiment Analysis
Module1:
Introduction to Power BI
Module2:
Data Preparation and Import
Module3:
Visualizations and Tiles
Module4:
Create a Report with Visualizations
Module5:
DAX functions
Module6:
DAX Formulas and Advanced Analysis
  • Get Started with Power BI
  • Overview: Power BI concepts
  • Sign up for Power BI
  • Data sources: Excel, databases, and files.
  • Power Query Editor: cleaning, shaping, merging, and appending data.
  • Understanding relationships: one-to-one, one-to-many, and many-to-many and creating and managing relationships between tables.
  • Explore the Power BI portal.
  • Overview: Visualizations
  • Using visualizations
  • Create a new report
  • Create and arrange visualizations
  • Format a visualization
  • Creating interactive reports and dashboards.
  • Choosing appropriate visualizations: charts, maps, and tables.
  • Formatting and customizing visuals to improve aesthetics and readability.
  • Create chart visualizations
  • Create a report using text, a map, and gauge visualizations.
  • Use a slicer to filter visualizations
  • Sort, copy, and paste visualizations
  • From the collection, save and utilize a unique image.
  • New DAX functions
  • Date and time functions
  • Time intelligence functions
  • Filter functions
  • Information functions
  • Logical functions
  • Math & Trig functions
  • Parent and child functions
  • Text functions
  • Writing DAX formulas for calculated columns, measures, and calculated tables.
  • Performing advanced calculations and aggregations using DAX functions.
  • Utilizing features like drill-down, drill-through, and cross-filtering for interactive exploration.
  • Creating hierarchies and implementing filtering options for deeper analysis.
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Data Science Syllabus

Python
Statistics
Machine Learning
Deep Learning
Natural language processing (NLP)
Power BI

Introduction to Python

  • Overview of Python- Starting with Python
  • Introduction to installation of Python
  • Introduction to Python Editors & IDE's (Canopy, pycharm, Jupyter, Rodeo, Ipython etcโ€ฆ)
  • Understand Jupyter notebook & Customize Settings
  • Concept of Modules/Libraries - Important packages (NumPy, SciPy, scikit-learn, Pandas, Matplotlib, etc)
  • Installing & loading Packages & Name Spaces
  • Data Types & Data objects/structures (strings, Tuples, Lists, Dictionaries)
  • List and Dictionary Comprehensions
  • Variable & Value Labels โ€“ Date & Time Values
  • Basic Operations - Mathematical - string - date
  • Reading and writing data
  • Control flow & conditional statements
  • Errors and exception handling
Accessing/Importing and Exporting Data using python modules
  • Importing Data from various sources (Csv, txt, excel, access etc.)
  • Database Input (Connecting to database)
  • Viewing Data objects - sub setting, methods
  • manipulating data
  • Combining data
  • Exporting Data to various formats
  • Important python modules: Pandas
Data Manipulation โ€“ cleansing โ€“ Munging using Python modules
  • Cleansing Data with Python
  • Data Manipulation steps(Sorting, filtering, duplicates, merging, appending, subsetting, derived variables,
  • sampling, Data type conversions, renaming, formatting etc)
  • Data manipulation tools(Operators, Functions, Packages, control structures, Loops, arrays etc)
  • Python Built-in Functions (Text, numeric, date, utility functions)
  • Python User Defined Functions
  • Normalizing data
  • Formatting data
  • Important Python modules for data manipulation (Pandas, Numpy, math, string, datetime etc)
  • Basic Statistics - Measures of Central Tendencies and Variance
  • Inferential Statistics -Sampling - Concept of Hypothesis Testing
  • Exploratory data analysis
  • Descriptive statistics, Frequency Tables and summarization
  • Creating Graphs- Simple plotting/Bar/pie/line chart/histogram/ boxplot/ scatter etc)
  • Important Packages for Exploratory Analysis(NumPy Arrays, Matplotlib, Pandas and scipy.stats etc)
  • Important modules for statistical methods: Numpy, Scipy, Pandas

Introduction to Machine Learning

  • Origin and the history of machine learning
  • Differences between AI and machine learning
  • Differences between data science, statistics, data mining and machine learning
  • Applications of machine learning
  • Limitations of machine learning
  • Machine learning is the future
Implementing machine learning
Machine Learning Process
  • Collecting data
  • Pre-processing and preparing data
  • Exploring data
  • Choosing a model
  • Training the model
  • Evaluating the model
  • Improving the performance of model
Machine Learning Theories and Algorithms
  • Meaning of algorithm
  • Importance of algorithms in machine learning
Types of Machine Learning Algorithms
  • Supervised learning
  • Unsupervised learning
  • Semi-supervised learning
  • Reinforcement learning
Supervised Learning Tasks and Algorithms
Classification
  • Nearest neighbor (non-parametric /instance-based)
  • Decision trees (non-metric /symbolic)
  • Naive bayes theorem (parametric /probabilistic)
Numeric Prediction
  • Linear Regression
  • Multiple Regression
  • Logistic Regression
  • Time Series Forecasting
Unsupervised Learning Tasks and Algorithms
Pattern detection
  • Association rules (rule based learning)
  • Apriori Algorithm
Clustering
  • K Means Clustering
  • Hierarchical clustering
Black Box Method
  • Support Vector Machines(SVM)
Ensemble Methods
  • Random Forest
  • Bagging
  • Boosting
Data Preprocessing in Python
  • Standardization and Normalization
  • Missing value replacement
  • Resampling
  • Discretization
  • Feature Selection
  • Dimensionality Reduction
  • Neural Networks (Perceptron, MLP)
  • Activation Functions (ReLU, Sigmoid, Tanh)
  • Loss Functions (MSE, Cross-Entropy)
  • Optimization (Gradient Descent, Adam, RMSprop)
  • Backpropagation
  • Convolutional Neural Networks (CNNs)
  • Recurrent Neural Networks (RNNs)
  • Long Short-Term Memory (LSTM) & Gated Recurrent Unit (GRU)
  • Transformers (Self-Attention Mechanism)
Fundamentals of NLP
  • Tokenization (Word & Sentence Tokenization)
  • Lemmatization & Stemming
  • Stopword Removal
  • Part-of-Speech (POS) Tagging
  • Named Entity Recognition (NER)
  • Regular Expressions for Text Processing
Text Representation Techniques
  • Bag of Words (BoW)
  • Term Frequency-Inverse Document Frequency (TF-IDF)
  • Word Embeddings (Word2Vec, GloVe, FastText)
  • Contextual Embeddings (ELMo, BERT, GPT)
Syntactic & Semantic Processing
  • Dependency Parsing
  • Constituency Parsing
  • Semantic Role Labeling (SRL)
  • Coreference Resolution
Classical NLP Techniques
  • Text Classification (Naรฏve Bayes, SVM, Random Forest)
  • Sentiment Analysis

Introduction to Power BI

  • Get Started with Power BI
  • Overview: Power BI concepts
  • Sign up for Power BI
Data Preparation and Import
  • Data sources: Excel, databases, and files.
  • Power Query Editor: cleaning, shaping, merging, and appending data.
  • Understanding relationships: one-to-one, one-to-many, and many-to-many and creating and managing relationships between tables.
  • Explore the Power BI portal.
Visualizations and Tiles
  • Overview: Visualizations
  • Using visualizations
  • Create a new report
  • Create and arrange visualizations
  • Format a visualization
  • Creating interactive reports and dashboards.
  • Choosing appropriate visualizations: charts, maps, and tables.
  • Formatting and customizing visuals to improve aesthetics and readability.
Create a Report with Visualizations
  • Create chart visualizations
  • Create a report using text, a map, and gauge visualizations.
  • Use a slicer to filter visualizations
  • Sort, copy, and paste visualizations
  • From the collection, save and utilize a unique image.
DAX functions
  • New DAX functions
  • Date and time functions
  • Time intelligence functions
  • Filter functions
  • Information functions
  • Logical functions
  • Math & Trig functions
  • Parent and child functions
  • Text functions
DAX Formulas and Advanced Analysis
  • Writing DAX formulas for calculated columns, measures, and calculated tables.
  • Performing advanced calculations and aggregations using DAX functions.
  • Utilizing features like drill-down, drill-through, and cross-filtering for interactive exploration.
  • Creating hierarchies and implementing filtering options for deeper analysis.
Our Candidates
Candidate Profile
  • Professionals with adequate mathematical, logical, and analytical aptitude.
  • Fresh graduates wanting a career in Big Data or Data Science.
  • Database aspirants wishing to explore the world of Big Data.
  • Managers from diverse fields want to sharpen their analytical skills.
  • Software developers are aspiring to become data scientists and business analysts.
  • Hadoop experts who want to learn R and Machine Learning execution.
  • Statisticians who want to apply big data statistics techniques.
  • Information architects wishing to specialise in predictive analysis.
  • Analysts want to master data science concepts.
Our Trainers
Trainer Profile
  • Expert and certified IT professionals with 12 + years of experience
  • Committed individuals who are willing to go the extra mile to help students succeed.
  • Trainers who provide one-to-one consultation and adopt a personalised approach to learning.
  • Offers in-depth training in Data Science & AI to help you stay informed and updated.
  • Approachable and ready to answer all your queries related to data science & Artificial
  • Intelligence. Cover all concepts from basics to make every student an expert in data science and related topics.

Enrol for Data Science Certification Course in Chennai

Aimoreโ€™s Data Science Course in Chennai sharpens your skills and gives you the practical and theoretical knowledge you need to land lucrative data science roles. Adding to your arsenal of skills is our Data Science Certification, awarded upon completion of our theory and practical sessions.

And thereโ€™s more! Our training prepares you to ace globally acclaimed industry certification exams that add incredible value to your portfolio. The list of certifications includes:

  • SAS Certified Data Scientist
  • Dell EMC Data Science Certification
  • TensorFlow Developer Certification
  • Amazon AWS Big Data Certification
  • IBM Data Science Professional Certification
  • Google Professional Data Engineer Certification
  • Microsoft Certified Azure Data Scientist Associate Certification

With an impressive success rate among our alumni, you'll gain a unique edge in your job search, setting you apart from the competition!

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Data Science Courses With Aimore Technologies

Machine Learning
Artificial Intelligence
Hadoop
Deep Learning
Apache Spark

Machine Learning is the next best thing in technology, making waves in the tech world. Aimoreโ€™s data science training in Chennai focuses on upskilling our candidates to excel in their domains and refine their capabilities to face real-world scenarios at work. Our ML training is completely hands-on, which is a bonus.

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Machines demonstrate a great deal of intelligence, and everyone finds it fascinating. A certification in Artificial Intelligence can catapult your professional life to greater heights, which is why it is one of the most trending courses. Aimoreโ€™s AI course, combined with Deep Learning, can make you an expert in building powerful AI algorithms and more.

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To learn how to handle Big Data, you need to understand Hadoop. Hadoop is a platform used to handle deep analytics and retrieve huge amounts of data from diverse applications. Aimoreโ€™s Hadoop training will help you understand how to use the platform in the best possible way.

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Deep Learning is a perfect combination of Artificial Intelligence and Machine Learning. Aimoreโ€™s training in Deep Learning covers AI concepts and implementing ML algorithms with deep networks, neural networks, and Deep Learning frameworks. You will also get hands-on training and skills training from our accredited instructors.
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A professional exploring Deep Learning using the power of Machine Learning and Artificial Intelligence.

Knowledge of Apache Spark is essential because it comes with high-level APIs for Python, R, Scala, and Java. Furthermore, it is a hundred times faster than Big Data Hadoop and ten times faster than a disk drive. Our data science course in Chennai with placement is advantageous because it covers the syllabus according to current IT trends.

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Transform Your Career with Placement Guarantee Data Science Course

Placement in top companies
Live projects & certification
Resume preparation
Free technical support after course completion
Experiential learning through projects
Regular mock interviews
Free laboratory facilities
Free Wifi facility
Option to earn income through blogging
Trial classes to help you learn
Insightful lab exercises
Located in Chennai's IT hub

Chennai's Choice for Fast Data Science Skills

Fast-track your career with industry experts and an up-to-date syllabus through Aimoreโ€™s data science training. Get job-ready faster โ€“ 78% of our graduates finish in 6 months, aligning with industry needs to boost your career quickly.
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Frequently Asked Questions about Chennai Data Science Training

The modern technical industry uses data science to analyse data and make smart predictions. It is a relatively new field with immense potential.

With a deep understanding of Data Science and a clear grasp of the required skill set, you can easily find fruitful career opportunities. The Data Science field is expected to keep growing in the coming years, making it an ideal option for anyone looking for great career opportunities.

Aimoreโ€™s data science course provides you with:

  • In-depth knowledge of Data Science.
  • Detailed insights about data mining and statistics
  • Knowledge and understanding of decision tree creation.
  • Ability to understand big data concepts
  • Skills to use the tableau and map-reduce.
Not effectively. Data science involves managing massive volumes of data, and mathematical knowledge and skills are needed to do that properly. Expertise in linear algebra, statistics, and calculus helps significantly in analysing data and performing core data science tasks.

To excel as a data scientist, you will need:

  • Programming language skills
  • Higher educational degrees and certifications
  • Knowledge of Hadoop and Apache Spark
  • Knowledge of AI and ML
  • Understanding of Natural Language Processing
  • Knowledge of Computer Vision

Aimoreโ€™s data science training prepares you for all this and more.

Data science involves complex topics like ML, AI, and programming, so it requires dedicated effort. However, Aimore's data science training in Chennai uses hands-on practice, expert guidance, and real-world projects to make it manageable and help you succeed.

In this course, you will gain a comprehensive understanding of the concepts and tools related to data science. As you finish the course, you will learn how to analyse and use data. You will also learn to create predictive models and convey the findings effectively. You will also be able to showcase your skills in real-time projects.

Absolutely! Coding is a crucial skill for task automation, analysis customisation, model-building, data manipulation, and handling complex data operations efficiently, as is your proficiency in languages like R and Python.

Coding is a basic requirement for most job roles in data science, particularly as you progress in your career. Our data science training in Chennai provides in-depth instructions to hone your coding skills and programming language proficiency.

Our course is open to all graduates with analytical thinking (from fields like Science, Engineering, Economics, and Mathematics)โ€”though a background in Mathematics, Computer Science, or Statistics is beneficial. Connect with us to determine whether our Data Science Course in Chennai is the right choice for your career.

Salaries within the data science field depend on your specialisation, skills, and experience. High-paying jobs in this field are awarded to individuals with exceptional skills in:

  • Machine Learning
  • Deep Learning
  • Generative AI
  • Big Data tools like Hadoop and Spark

Positions such as Data Scientists, ML Engineers, and AI Specialists rank among the highest earners in this industry.

At Aimore, we prepare you to bag the top data science jobs and enhance your earning potential with our hands-on training and placement support.

The ideal Data Science Course integrates theoretical and practical knowledge with adequate exposure to real-world tools. Aimoreโ€™s Data Science Course in Chennai is reputed for its extensive curriculum encompassing:

  • Power BI
  • Statistics
  • Python
  • Machine Learning
  • Deep Learning
  • Natural Language Processing

Our training equips you to ace globally recognised certification exams like those offered by tech giantsโ€”Microsoft, IBM, and Google. Furthermore, our flexible schedules, anytime guidance from our expert trainers, and 100% placement assistance create a well-rounded educational experience.

The Data Science Course offered at Aimore Technologies extends for 4 months, depending on whether you choose to attend the course during the weekdays or on weekends. We offer flexible schedules and fast-track options to quickly advance your training and become job-ready in just a few months. Our hybrid learning model ensures that you maintain consistency and confidence throughout your course.

While there are no strict prerequisites, the following will help you succeed in the field of data science:

  • Strong fundamentals in mathematics, logical reasoning, and statistics.
  • Familiarity with programming concepts, especially Python.

Fortunately, Aimoreโ€™s Data Science course in Chennai covers everything you need to ace your career in data science. Hence, it is ideal for beginners and established professionals, irrespective of whether you are from an IT background or not.

Do not doubt itโ€”data science remains one of the most in-demand career paths in the global IT industry, with applications across diverse sectors such as:

  • Healthcare
  • Finance
  • Technology
  • E-commerce

Moreover, the rise of AI and Big Data is driving the need for skilled professionals capable of deriving meaningful insights from data and enabling informed business decisions. Aimoreโ€™s data science training in Chennai places you well ahead of the curve with a future-ready curriculum and placement support.

Of course! Aimoreโ€™s Data Science course is open to all aspiring candidates, regardless of their academic and professional backgrounds. Our structured curriculum covers everythingโ€”it guides learners from the basics of Python programming to advanced machine learning (ML) techniques.

Under our guidance, mentorship, and hands-on training, anyone can successfully transition into a fulfilling career in data science, regardless of prior experience in IT.

Aimore Technologies ยท Data Science Course In Chennai - Aimore Technologies
Aimore Technologies ยท data science course in Chennai - Aimore Technologies
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