Our Data Science Certification Training is a structured, hands-on program designed to equip participants with the essential skills and knowledge required to excel in Data Science. The course covers Python, Machine Learning, AI, Data Analytics, Big Data, and more, ensuring you are well-prepared for leading Data Science certifications like:

• IBM Data Science Professional Certificate
• Google Data Analytics Professional Certificate
  
• Microsoft Azure Data Scientist (DP-100)
• DASCA Certified Data Scientist (CDS)
• SAS Certified Data Scientist

• Beginners & Students interested in Data Science
  
• IT Professionals looking to transition into Data Science
  
• Analysts & Engineers wanting to enhance Data Science skills
  
• Business & Marketing Professionals interested in Data Analytics
  
• Anyone preparing for a Data Science Certification

• Comprehensive Hands-on Training with Real-world Projects
• Expert-Led Sessions by Industry Professionals
• Live Online / Classroom / Hybrid Learning Options
• Mock Tests & Certification Exam Preparation
• Dedicated Career Support & Placement Assistance

Introduction to Data Science
Understanding Data Science & Its Applications
Data Science vs. Data Analytics vs. Machine Learning
Tools & Technologies Used (Python, R, SQL, etc.)

Python & R for Data Science
Python Basics: Variables, Loops, Functions
Data Manipulation with Pandas & NumPy
Data Visualization with Matplotlib & Seaborn
R Programming Basics & Statistical Analysis

Data Analysis & Exploratory Data Analysis (EDA)
Data Cleaning & Preprocessing
Handling Missing Data & Outliers
Feature Engineering & Data Transformation

Statistics & Probability for Data Science
Descriptive & Inferential Statistics
Probability Distributions & Hypothesis Testing
Regression Analysis & Correlation

Machine Learning Fundamentals
Supervised vs. Unsupervised Learning
Regression Models (Linear, Logistic, Polynomial)
Classification Algorithms (Decision Trees, Random Forest, SVM)
Clustering (K-Means, Hierarchical Clustering)

Deep Learning & Neural Networks
Introduction to Neural Networks & Deep Learning
TensorFlow & Keras for Model Development
Convolutional Neural Networks (CNNs)
Recurrent Neural Networks (RNNs)

Natural Language Processing (NLP)
Text Preprocessing (Tokenization, Lemmatization)
Sentiment Analysis & Named Entity Recognition
Topic Modeling & Text Classification

Big Data & Cloud Computing
Introduction to Hadoop, Spark & Big Data Tools
Cloud Computing for Data Science (AWS, Google Cloud, Azure)
Handling Large Datasets & Distributed Computing

AI & Advanced Machine Learning
Reinforcement Learning Fundamentals
Transfer Learning & AutoML
Generative AI (ChatGPT, BERT, GANs)

Capstone Project & Certification Preparation
Real-World Data Science Project
Mock Exams for Data Science Certifications
Resume Building & Interview Preparation