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NASSCOM Futureskills Prime Certified Advanced Data Science with Python Program including Free Internship & Best Placement Support
Data is the fuel of the 21st Century.
This advanced NASSCOM FutureSkills Prime Certified Data Science course in Hyderabad guarantees career transformation. Here’s a one-time opportunity to learn with the best Data Science training in Hyderabad. Gain knowledge of data analytics, tools, and operations for data science certification and meet the massive demand for these skills.
Here you will learn to read, analyze, clean, engineer, and present data in a way that promotes the growth of your business. To drive data and extract significant results, this Data Science course can help you progress in leaps and bounds. This NASSCOM FutureSkills Prime Certified Data Science training will accelerate your career as it covers relevant topics & pushes you to work on real-time scenarios.
Artificial Intelligence and Machine Learning in Data Science technology are constantly revolutionizing the industry by innovating and solving complex business problems. Innomatics Research Labs is a hub of advanced training in such technologies.
Our principle of holistic development lies in the strong bedrock that believes in the amalgamation of theoretical knowledge along with practical training. This makes us the best Data Science course in Hyderabad.
GLIMPSES OF OUR VICTORY – Successfully Placed Innominions
NASSCOM FutureSkills Prime Certified Advanced Data Science with Python Course Curriculum (Syllabus)
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Module 1: Python Core & Advanced
INTRODUCTION
- Variables, Data Types, and Strings
- Lists, Sets, Tuples, and Dictionaries
Control Flow and Conditional StatementFunctions and ModulesFile Handling
Class and Objects
Module 2: Data Analysis using Python
Numpy – NUMERICAL PYTHO
Data Manipulation with Pandas
DATA VISUALIZATION
Data Visualization using Matplotlib and Pandas
Exploratory Data Analysis
UNSTRUCTURED DATA PROCESSING
Regular Expressions
Project On Web Scraping: Data Collection And Exploratory Data Analysis
Module 3: Advanced Statistics
Introduction to Statistics and Data Types
Descriptive Statistics
Probability Distribution
Inferential Statistics
Module 4. Data Base (SQL) + Reporting Tool (Power BI)
Introduction to SQL
Data Exploration and Data Filtering (DQL and OPERATORS)
SQL Fundamentals
SQL Database Objects
Advanced Topics
Introduction To Power BI
Data Import And Data Visualizations
Power Queries
Power Pivot And Introduction To Dax
Data Analysis Expressions
Login, Publish To Web And RLS
Miscellaneous Topics
Module 5: Machine Learning - Supervised & Un-Supervised Learning
Introduction
Validation Methods
Supervised Learning
Probability-Based Approach – Naive BayesPolynomial Regression
Introduction And Linear Algebra
Distance Based Approach – K Nearest Neighbors
Rule / Decession Boundary Based Approach – Decision Trees
Boundary-Based Linear Model – Linear Regression
Multiple Linear Regression
Evaluation Metrics for Regression Techniques
Polynomial Regression
Regularization Techniques
Logistic regression
Support Vector Machines
Ensemble Methods in Tree Based Models
Random Forest
Boosting: Adaboost, Gradient Boosting, XG Boosting:
Machine Learning Applications for Data Analysis
Un Supervised Learning
Dimensionality Reduction Techniques – PCA & t-SNE
K-Means Clustering
Hierarchical Clustering
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Module 6: Deep Learning
Introduction to Deep Learning Principal Components Analysis
Neural Network Architecture and Activation Functions
Forward and Backward Propagation Optimizers
Neural Network Architecture and Activation Functions
Keras Hands-on – Regression and Classification
Module 7: CNN & Computer Vision
Intro to Images and Image Preprocessing with OpenCV CNN Architecture
Image Classification Case Study
Transfer Learning
Case Study with Transfer Learning
Object Detection
YOLO – Case Study
Module 8: Natural Language Processing
Introduction to text and Text Preprocessing with nltk and spacy
Vectorization Techniques
Project – Text Classification
RNNs
Project – Sequence Tagging
LSTMs
Auto Encoders
Transformer and Attention
BERT
Module 9: Gen AI
Intro To Gen AI
Intro To LLM
Prompt Engineering and Working with LLM
Open AI
Gemini
LLaMA
LangChain
Languages & Tools Covered in Data Science course
Why Innomatics Stands Out the Best!
Why Data Science at Innomatics Research Labs?
- 500+ Industry experts from Fortune 500 companies
- Dedicated In-house data scientist team accessible round the clock
- 200+ Hours of intensive practical-oriented training
- Flexible Online and Classroom training sessions
- 5+ Parallel Data science batches running currently on both weekdays & weekends
- Backup Classes and Access to the Learning Management System (LMS)
- One-to-one mentorship and Free Technical Support
- FREE Data science Internshipon our projects & products
- Projects and use cases derived from businesses
- 30+ POCsand use cases to work, learn, and experiment
- Bi-weekly Industry connections from industry experts from various sectors
- Opportunity to participate in Meet-ups, Hackathons, and Conferences
- Dedicated training programs for NON-IT professionals
- Besr placement Support
- Globally Recognized Certification from NASSCOM FutureSkills Prime
