CoursesData ScienceData Science with AI
CID11015

Data Science with AI

This comprehensive course equips learners with Python programming, NumPy, Pandas, and Matplotlib for data manipulation and visualization. Dive into machine learning, deep learning, NLP, and computer vision. Master Azure for MLOps to deploy and manage ML models. Prepare for a data science career with hands-on projects and real-world skills.

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duration

110 Hours

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NEXT BATCH

Jun 05, 2024

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mode

Online

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payment options

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Programoverview

Program Overview

Explore data science and AI journey from Python basics to advanced machine learning and deep learning. Analyze data, visualize insights, and build AI models with industry-standard tools.

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Master in-demand skills for extracting insights from data and building AI models

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Learn to use popular tools and libraries such as Python and Keras

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Understand how to apply AI techniques to real-world problems and make data-driven decisions

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Open up career opportunities in data science, AI engineering, and related fields

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Eligiblility

Basic understanding of mathematics, statistics, and programming. Python familiarity is beneficial but not mandatory. Open to students, professionals, and enthusiasts passionate about data science.

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Why should you learn?

Upon completion, learners gain comprehensive Python, NumPy, Pandas, and Matplotlib skills for data manipulation and visualization. Acquire ML, DL, NLP, and CV skills for complex data challenges and data science careers.

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Possible Job Roles

Upon course completion, learners can pursue diverse data science roles such as Data Analyst, Data Scientist, Machine Learning Engineer and AI engineer.

Salary Range

4 to 20 Lakhs Per Annum

Course-modules

Course Modules

110 Hours COURSE

6 hours

Python For Data Science

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The "Python" module covers basic programming concepts, string manipulation, data structures, date/time operations, and file handling, suitable for non-IT students.
  • Introduction to Python Programming

  • Variables, local and global variables, loops, functions, programming exercises

  • Python Strings

  • Operators Lists, Tuples, Dictionary, Date&Time,- Files I/O Exceptions

3 hours

NUMPY (Numerical Python)

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The "NUMPY" module covers ndarray operations, universal functions, statistical functions, indexing, slicing, and advanced operations for numerical computing.
  • Ndarray Object

  • Numpy arrays-Basic Operations,Universal Functions

  • Arange, linspace, logspace Indexing and Slicing Statistical Functions Dot Products

  • Matrix Multiplication

5 hours

Pandas

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The "Pandas" module covers Series and DataFrames, focusing on creation, manipulation, and essential functionalities for efficient data analysis.
  • Series

  • DataFrames

4 hours

Data Visualisation using Mathplotlib

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The "Data Visualization with Matplotlib" module teaches core principles and techniques for creating effective visualizations, progressing to advanced charting.
  • Principles of Information Visualisation

  • Basic Charting

  • Charting Fundamentals

  • Applied Data Visualizations

5 hours

Machine Learning using sklearn

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In "Machine Learning with sklearn," explore regression, classification, and clustering using various algorithms, enhancing machine learning model building skills.
  • Regression

  • Classification

  • Clustering

4 hours

Deep Learning using TensorFlow and Keras

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Explore advanced neural network concepts, including CNNs for image processing, RNNs for sequence data, and LSTMs for long-term dependencies.
  • Introduction to Perceptron and Neural Networks (ANN)

  • CNN

  • RNN

  • LSTM

6 hours

NLP using NLTK and Spacy

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Learn NLP fundamentals, including text tokenization, word lemmatization, semantics with word vectors, stop words, and sentiment analysis.
  • NLP Introduction and Basics

  • Tokenization

  • Lemmatization

  • Semantics and word vectors

  • Stop words

  • Sentimental Analysis

5 hours

Computer Vision using cv2

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Explore image processing and computer vision essentials, including image/video manipulation, color/shape/face detection, and number plate extraction using OpenCV.
  • Image processing and Computer Vision basics

  • Loading Images and Videos

  • Color and Shape detection

  • Face detection

  • Number plate detection

3 hours

Generative AI for Data Science

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Explore Prompt Engineering techniques and integrate Generative AI into the data science life cycle for data generation and analysis.
  • Introduction to Gen AI and LLM

  • Prompt Engineering

  • Data Science life cycle using Gen AI

5 hours

Azure for Data Science with MLOPs

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Discover Azure tools for training ML models, orchestrating pipelines, deploying batch inference pipelines, and monitoring performance for efficient ML solutions.
  • Training ML models in Azure

  • Automating ML models

  • Orchestrating Pipelines

  • Deploying batch inference pipelines

  • Monitoring Performance

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Certification of Completion

Certifies completion of data science course, covering fundamentals, machine learning, data analysis, and visualization.

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Program Cohorts

Jun 2024 Batch

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Admission Process at Cokonet

The course admission process at Cokonet involves streamlined procedures ensuring efficient enrollment for prospective students.

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Speak With our Career Counselor

Our career counselor will help you identify the suitable course for you.

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Complete Payment

Finalize the transaction securely, using the provided payment methods.

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Get Enrolled

Enroll in the chosen course, providing personal details and payment information

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Our intelligence is what makes us human, and AI is an extension of that quality.

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Financing & Support

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0% Interest Loans

Access 0% interest loans (6/9/12 Months EMI) for your education, ensuring affordability while you pursue your dreams.

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Pay in Installments

Ease your financial burden with our convenient installment payment options.

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Scholarships

We believe in supporting aspiring learners by providing financial aid to help them pursue their dreams.

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Laptop Support

Seamless assistance with our comprehensive laptop support services.

Data Science with AI: Frequently Asked Questions (FAQs)

Concerns regarding our Data Science course? Find the answers to the questions you often ask

Basic knowledge of mathematics, statistics, and programming concepts is recommended but not mandatory.