Course Provider
What will you learn in this course?
- Work with various data generation sources
- Perform Text Mining to generate Customer Sentiment Analysis
- Analyse structured and unstructured data using different tools and techniques
- Develop an understanding of Descriptive and Predictive Analytics
- Apply Data-driven, Machine Learning approaches for business decisions
- Build models for day-to-day applicability
- Perform Forecasting to take proactive business decisions
- Use Data Concepts to represent data for easy understanding
Certificate Course on Data Science
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Skill Type
Emerging Tech -
Domain
AI/ BDA -
Course Category
Deepskilling Course - Placement Assistance
Yes
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Certificate Earned Joint Co-Branded Participation Certificate & Partner Completion certificate -
Nasscom Assessment Available -
Course Covered under GoI Incentive
Yes -
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Course Price
INR 70,000INR 55,000till 30th Sep 2023 -
Course Duration
184 Hours
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Why should you take this course?
- This Data Science Course in India lends focus to Machine Learning algorithms like k-NN Classifier, Decision Tree and Random Forest, Ensemble Techniques- Bagging and Boosting, AdaBoost, Extreme Gradient Boosting, and Naive Bayes algorithm.
- Text Mining and Natural Language Processing also feature in the course curriculum.
- The building blocks of Neural Networks -ANN and Deep Learning Black Box Techniques like CNN, RNN, and SVM are also described in great detail.
- The concluding modules include model-driven and data-driven algorithm development for forecasting and Time Series Analysis. This is the most comprehensive data science course from the best data science training institute in India.
Who should take this course?
- IT Engineers
- Data and Analytics Manager
- Business Analysts
- Data Engineers
- Banking and Finance Analysts
- Marketing Managers
- Supply Chain Professionals
- HR Managers
- Math, Science and Commerce Graduates
Curriculum
- CRISP – DM - Project Management Methodology
- Exploratory Data Analytics (EDA) / Descriptive Analytics
- Statistical Data Business Intelligence and Data Visualization
- Plots & Inferential Statistics
- Probability Distributions (Continuous & Discrete)
- Hypothesis Testing - The ‘4’ Must Know Hypothesis Tests
- Data Mining Supervised Learning – Linear Regression, OLS
- Predictive Modelling – Multiple Linear Regression
- Lasso and Ridge Regressions
- Logistic Regression – Binary Value Prediction, MLE
- Multinomial Regression
- Advanced Regression for Count Data
- Machine Learning - k -NN Classifier
- Decision Tree & Random Forest
- Ensemble Techniques - Bagging and Boosting
- AdaBoost & Extreme Gradient Boosting
- Text Mining and Natural Language Processing (NLP)
- Machine Learning Classifier Technique - Naive Bayes
- Introduction to Perceptron and Multilayer Perceptron
- Building Blocks of Neural Network - ANN
- Deep Learning Primer
- Kernel Method - SVM
- Data Mining Unsupervised Learning – Clustering
- Data Mining Unsupervised Learning - Dimension Reduction (PCA)
- Data Mining Unsupervised Learning - Association Rules
- Recommendation Engine
- Network Analytics
- Auto Machine Learning (Auto ML)
- Survival Analytics
- Forecasting/Time Series – Model-Driven Algorithms
- Forecasting/Time Series - Data-Driven Algorithms
Tools you will learn in this course
Python thru (Anaconda Spyder, Jupyter Notebook)) google Colab
FAQs
Different organisations use different terms for data professionals. You will sometimes find these terms being used interchangeably. Though there are no hard rules that distinguish one from another, you should get the role descriptions clarified before you join an organisation.
With growing demand, there is a scarcity of Data Science Professionals in the market. If you can demonstrate strong knowledge of Data Science concepts and algorithms, then there is a high chance for you to be able to make a career in this profession.
360DigiTMG provides internship opportunities through Innodatatics, our USA-based consulting partner, for deserving participants to help them gain real-life experience. This greatly helps students to bridge the gap between theory and practical.
In this blended programme, you will be attending 184 hours of classroom sessions of 6 months. After completion, you will have access to the online Learning Management System for another three months for recorded videos and assignments. The total duration of assignments to be completed online is 150+ hour. Besides this, you will be working on 2 live projects for a month.
There are plenty of jobs available for data professionals. Once you complete the training, assignments and the live projects, we will send your resume to the organisations with whom we have formal agreements on job placements. We also conduct webinars to help you with your resume and job interviews. We cover all aspects of post-training activities that are required to get a successful placement.