Best Data Science Course – Learn AI, Machine Learning & Data Analytics

Become a Certified Data Scientist & Master AI & ML

Are you looking for the best data science course to kickstart your career in Artificial Intelligence (AI), Machine Learning (ML), and Data Analytics? At TRAINING TRAINS, we offer a comprehensive Data Science Training Program that covers Python, R, SQL, Machine Learning, Deep Learning, Big Data, and Business Analytics.

Learn from industry experts, work on real-world projects, and become job-ready in just 3 to 6 months!

Why Choose Our Data Science Course?

  • Industry-Relevant Curriculum – Covers Data Science, AI, ML, Deep Learning & Big Data.
  • Hands-on Training – Work on real-world datasets & live projects.
  • Expert Mentors – Learn from data science professionals & AI engineers.
  • 100% Placement Assistance – Resume building, interview prep & job referrals.
  • Flexible Learning – Online & offline classes with weekend & fast-track options.
Join the No.1 Data Science Training Program & Build a Future in AI & ML!
Have any questions? Feel free to Contact us at Anytime
  • +91 9698548633

Data science course @ erode

What You’ll Learn – Data Science Course Syllabus

  • What is Data Science?

  • Applications of Data Science

  • Data Science vs. Machine Learning vs. AI

  • Tools & Technologies in Data Science

  • Setting up the environment (Jupyter Notebook, Anaconda, Google Colab)

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  • Python Basics (Variables, Data Types, Operators)

  • Control Structures (Loops, Conditional Statements)

  • Functions and Modules

  • Object-Oriented Programming in Python

  • Python Libraries: NumPy, Pandas, Matplotlib, Seaborn

  • Data Preprocessing (Handling Missing Values, Outliers, etc.)

  • Data Cleaning using Pandas

  • Exploratory Data Analysis (EDA)

  • Data Visualization using Matplotlib & Seaborn

  • Feature Engineering & Selection

  • Descriptive Statistics (Mean, Median, Mode, Variance, Standard Deviation)

  • Probability Theory

  • Probability Distributions (Normal, Binomial, Poisson)

  • Hypothesis Testing & Confidence Intervals

  • Correlation & Covariance

  • Introduction to Machine Learning

  • Supervised vs. Unsupervised Learning

  • Regression Models (Linear, Polynomial, Ridge, Lasso)

  • Classification Models (Logistic Regression, KNN, SVM, Decision Trees, Random Forest)

  • Clustering Techniques (K-Means, Hierarchical Clustering, DBSCAN)

  • Model Evaluation Metrics (Confusion Matrix, Precision, Recall, F1-score, AUC-ROC)

  • Hyperparameter Tuning (Grid Search, Random Search, Bayesian Optimization)

  • Ensemble Learning (Bagging, Boosting, Stacking)

  • Feature Scaling & Dimensionality Reduction (PCA, t-SNE)

  • Time Series Analysis (ARIMA, Prophet)

  • Introduction to Neural Networks

  • Activation Functions & Optimizers

  • Forward & Backpropagation

  • Convolutional Neural Networks (CNN) for Image Processing

  • Recurrent Neural Networks (RNN) & LSTMs for Sequence Data

  • Hands-on Projects with TensorFlow & Keras

  • Text Processing (Tokenization, Stemming, Lemmatization)

  • Bag of Words (BoW) & TF-IDF

  • Sentiment Analysis & Named Entity Recognition

  • Word Embeddings (Word2Vec, GloVe, BERT)

  • Chatbots & Text Generation

  • Introduction to Big Data Technologies

  • Apache Hadoop & Spark for Data Processing

  • Working with Google Cloud & AWS for Data Science

  • Data Storage Solutions (MongoDB, SQL, NoSQL)

  • Model Deployment using Flask & FastAPI

  • Docker & Kubernetes for ML Model Deployment

  • CI/CD for ML using GitHub Actions

  • AutoML & MLflow for Model Tracking

  • Real-world Data Science Projects

  • Resume Building & Portfolio Development

  • Mock Interviews & Technical Discussions

  • LeetCode, Kaggle Challenges

Who Should Join This Course?

  • Beginners & Freshers – No prior coding experience required.
  • IT Professionals & Engineers – Upgrade your career with AI & ML skills.
  • Data Analysts & Business Professionals – Learn data-driven decision-making.
  • Students & Job Seekers – Secure high paying jobs in data science.

Career Opportunities After Course Completion

  • Data Scientist
  • Machine Learning Engineer
  • AI Engineer
  • Big Data Analyst
  • Business Intelligence Analyst
  • Deep Learning Specialist

Top Companies Hiring Data Scientists: Google, Microsoft, Amazon,TCS, Infosys, IBM, Deloitte & More!

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