Data Science

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Unlock the future of tech πŸš€ – learn, grow, and succeed with our expert-led online courses! | Unlock the future of tech πŸš€ – learn, grow, and succeed with our expert-led online courses! | Unlock the future of tech πŸš€ – learn, grow, and succeed with our expert-led online courses! |
Unlock the future of tech πŸš€ – learn, grow, and succeed with our expert-led online courses! | Unlock the future of tech πŸš€ – learn, grow, and succeed with our expert-led online courses! | Unlock the future of tech πŸš€ – learn, grow, and succeed with our expert-led online courses! |

Data Science with AI Course – Learn Python, ML, Deep Learning & More

Master Data Science, Machine Learning & Artificial Intelligence with Hands-on Training in Hyderabad or Online

Level

Eligibility

Duration

Modules

All Levels(IT/Non-IT)

Any Graduation

5 Months

25+

Course Highlights

Full Course Material

Daily Assignments

Weekly Assessments

Quiz and Real Time Puzzles

Hands-on Industry Based Projects

Mock Interviews

Resume Preparation

1:1 technical support with 100% Placement Assistance

Download curriculum by filling form


    πŸ€– Why Learn Data Science with AI in 2024?
    Data is the new oilβ€”and Data Science powered by AI is the engine that extracts value from it. From predictive analytics to self-learning algorithms, businesses are embracing data science to gain a competitive edge. This course trains you in Python, Machine Learning, Deep Learning, NLP, and more, helping you build AI-powered applications from scratch.

    πŸš€ Career Opportunities in Data Science & AI
    βœ” Data Scientist
    βœ” AI Engineer
    βœ” Machine Learning Developer
    βœ” Data Analyst (with AI exposure)
    βœ” NLP Engineer
    βœ” Computer Vision Specialist

    🧠 What You’ll Learn – Course Curriculum

    Foundations of Python for Data Science
    βœ… Python Basics – Syntax, Loops, Functions
    βœ… Data Structures & Libraries – NumPy, Pandas
    βœ… Data Cleaning, Transformation & Analysis

    Statistics & Analytics Core
    βœ… Descriptive & Inferential Statistics
    βœ… Hypothesis Testing – ANOVA, t-test, chi-square
    βœ… Data Visualization – Seaborn, Matplotlib

    Machine Learning with Python
    βœ… Supervised & Unsupervised Learning
    βœ… Regression, Classification, Clustering Algorithms
    βœ… Model Evaluation – Confusion Matrix, ROC

    Deep Learning & Neural Networks
    βœ… Introduction to Deep Learning
    βœ… ANN, CNN, RNN Architectures
    βœ… Keras & TensorFlow Implementation

    AI Specializations
    βœ… Natural Language Processing (NLP) – Tokenization, Sentiment Analysis
    βœ… Computer Vision – Image Classification, Object Detection
    βœ… Intro to Power BI – For Business Dashboards & Analytics

    πŸ‘©β€πŸ’Ό Who Should Take This Course?
    βœ” B.Tech / BSc / MCA / MBA graduates
    βœ” Python programmers interested in AI
    βœ” Working professionals in IT, analytics, or engineering
    βœ” Data enthusiasts & career switchers
    βœ” Freelancers & entrepreneurs building AI products

    🎯 Why Choose BEST IT Academy?
    πŸ”Ή Industry-expert instructors from AI/ML backgrounds
    πŸ”Ή Real-world datasets & capstone projects
    πŸ”Ή AI case studies – From healthcare to e-commerce
    πŸ”Ή Certification & Career Assistance
    πŸ”Ή Flexible Learning Modes & Affordable Pricing

    πŸ§‘β€πŸ’» Modes of Learning
    πŸ“ Hyderabad Classroom Training – Instructor-led in-person sessions
    🌐 Live Online Classes – Real-time virtual training
    πŸ“ Self-paced Access – Learn anytime with recorded materials

    Step into the Future of Intelligence
    With a strong foundation in Data Science and Artificial Intelligence, you’ll be ready to build cutting-edge solutions and make impactful decisions using data.

    πŸ“ž Contact Us for Batch Details & Fee Structure
    πŸ“ Hyderabad Center | 🌐 Online Training Available

    1. Introduction to Data Science

      • Overview of data science and its applications

      • Data science lifecycle

      • Role of a data scientist

    2. Data Collection and Cleaning

      • Data collection methods

      • Data cleaning and preprocessing techniques

      • Handling missing data

    3. Data Analysis and Visualization

      • Exploratory data analysis (EDA)

      • Data visualization tools and techniques

      • Creating insightful dashboards with Tableau

    4. Statistics and Probability

      • Fundamental concepts of statistics

      • Probability distributions

      • Hypothesis testing

    5. Machine Learning

      • Supervised and unsupervised learning

      • Model evaluation and selection

      • Hands-on projects with Scikit-Learn and TensorFlow

    6. Deep Learning

      • Neural networks and deep learning concepts

      • Building and training deep learning models

      • Applications of deep learning

    7. Big Data Technologies