IIT Madras - Advanced Certification in Data Science and AI
4.6 /5- Offered byIntellipaat
Advanced Certification in Data Science and AI at Intellipaat Overview
Duration | 7 months |
Total fee | ₹85,044 |
Mode of learning | Online |
Difficulty level | Intermediate |
Official Website | Go to Website  |
Credential | Certificate |
Advanced Certification in Data Science and AI at Intellipaat Highlights
- Earn a certificate after completion of course
- No Cost EMI Option
- 50+ Industry Projects & Case Studies
- 24*7 Support
Advanced Certification in Data Science and AI at Intellipaat Course details
- IT professionals looking for a career transition as Data Scientists and Artificial Intelligence Engineers
- Professionals aiming to move ahead in their IT career
- Artificial Intelligence and Business Intelligence professionals
- Developers and Project Managers
- Freshers who aspire to build their career in the field of Artificial Intelligence and Data Science
- Understand the issues and create models based on the data gathered, and also manage a team of Data Scientists
- Build strategies on frameworks and technologies to develop AI solutions and help the organization prosper
- With the help of several Machine Learning tools and technologies, build statistical models with huge chunks of business data
- Design and build Machine Learning models to derive intelligence for the numerous services and products offered by the organization
- Create and manage pluggable service-based frameworks that are customized in order to import, cleanse, transform, and validate data
- Extract data from the respective sources to perform business analysis, and generate reports, dashboards, and metrics to monitor the company performance
Master the skills of Machine Learning and Artificial Intelligence with this advanced Data Science and Artificial Intelligence by IIT Madras.
This online Data Science and Artificial Intelligence course aims to make you master in all the basic and advanced level skills in the various tools and technologies involved in the field of Data Science, Machine Learning, Deep Learning, and Artificial Intelligence.
This program helps you built capability of applying machine learning algorithms to solve complex business problems and how you can increase the accuracy of the model.
Advanced Certification in Data Science and AI at Intellipaat Curriculum
Preparatory Classes
Python & Linux
Module 1: Git
1.1 What is Version Control?
1.2 Types of Version Control System
1.3 Introduction to SVN
1.4 Introduction to Git
1.5 Git Lifecycle
1.6 Common Git commands
1.7 Working with branches in Git
1.8 Merging branches
1.9 Resolving merge conflicts
1.10 Git workflow
Module 2: Python with Data Science
2.1 Introduction to Data Science using Python
2.2 Python basic constructs
2.3 Statistics and probability
2.4 OOPs in Python
2.5 NumPy for mathematical computing
2.6 SciPy for scientific computing
2.7 Data manipulation
Module 3: Advanced Statistics
3.1 Central tendency
3.2 Variability
3.3 Hypothesis testing
3.4 Anova
3.5 Correlation
3.6 Regression
3.7 Probability definitions and notation
3.8 Joint probabilities
3.9 The sum rule, conditional probability, and the product rule
3.10 Bayes theorem
Module 4: Machine Learning & Prediction Algorithms
4.1 Machine learning using Python
4.2 Supervised learning
4.3 Unsupervised learning
4.4 Dimensionality reduction
4.5 Time-series forecasting
Module 5: Data Science at Scale with PySpark
5.1 Introduction to Big Data and Apache Spark
5.2 Apache Spark framework and RDDs
5.3 PySpark SQL and Data Frames
Module 6: AI & Deep Learning using TensorFlow
6.1 Introduction to Deep Learning and Neural Networks
6.2 Multi-layered Neural Networks
6.3 Artificial Neural Networks and various methods
6.4 Deep Learning libraries
Module 7: Deploying Machine Learning Models on Cloud (MLOps)
7.1 Need for MLOps
7.2 Deploying Machine learning programs in the production environment
7.3 Working with Jenkins & Docker for deploying Machine Learning solutions
Module 8: Data Visualization with Tableau
8.1 Introduction to data visualization
8.2 Architecture of Tableau
8.3 Working with metadata and data blending
8.4 Creation of sets
8.5 Working with filters
8.6 Organizing data and visual analytics
8.7 Working with mapping
8.8 Working with calculations and expressions
8.9 Working with parameters
8.10 Charts and graphs
8.11 Dashboards and stories
8.12 Tableau Prep
8.13 Integration of Tableau with R and Hadoop
Module 9: Data Science Capstone Project
Module 10: Data Analysis with MS Excel
10.1 Entering data
10.2 Referencing in formulas
10.3 Name range
10.4 Understanding logical functions & conditional formatting
10.5 Important formulas in Excel
10.6 Working with Dynamic table
10.7 Data transformation for analysis
10.8 Working with charts for data visualization
10.9 Pivot tables in Excel
10.10 Working with Macros in Excel and working with VBA
Module 11: Data Wrangling with SQL
11.1 Introduction to SQL
11.2 Database normalization and entity-relationship model
11.3 SQL operators
11.4 Working with SQL: Join, tables, and variables
11.5 Deep dive into SQL
11.6 Functions
11.7 Working with Subqueries
11.8 SQL views, functions, and stored procedures
Module 12: Natural Language Processing and its Applications
12.1 Overview of Natural Language Processing and text mining
12.2 Text mining, cleaning, and processing
12.3 Text classification
12.4 Sentence structure, sequence tagging, sequence tasks, and language modeling
12.5 Introduction to semantics and vector space models
Advanced Certification in Data Science and AI at Intellipaat Faculty details
Advanced Certification in Data Science and AI at Intellipaat Entry Requirements
- Education: Bachelor's degree from any recognized university
- Minimum 3 years of work experience
- Not mentioned
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