Course Provider
What will you learn in Certified Data Scientist course?
- A Certified Data Scientist is someone who has mastered the entire Data Science domain.
- The CDS course is specifically developed for those who are new to the data science field and wish to enter it with the greatest skills and assistance possible.
- Improve your understanding of the full Data Science project workflow.
- Learn the fundamentals of statistics.
- Practical experience with common machine learning techniques
- Data mining, data forecasting, and data visualization are all skills that you should have.
- Capable of putting up a business case for a Data Science project
Certified Data Scientist
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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 Coming Soon -
Course Covered under GoI Incentive
Yes -
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Course Price
INR 88,000+ 18% GST -
Course Duration
100 Hours
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Why should you take Certified Data Scientist course?
- The Certified Data Scientist is a thorough course that will teach you everything you need to know from the ground up, and it will be taught by an expert faculty with actual studies and coaching expertise.
- The Certified Data Scientist course is designed for both beginning and intermediate learners who want to get into the fast-paced world of data science.
- The CDS Program at DataMites is a career-oriented programme designed to instill a firm foundation in Data Science and everything related to it.
- Along with ML skills, the course would cover statistics, math, and python.
Who should take Certified Data Scientist course?
- This course is appropriate for recent graduates or students from any subject who want to improve their job prospects in the highly competitive data science industry.
- Working professionals interested in switching fields to data science.
- Strongly advised for anyone interested in data analytics and machine learning employment.
- Project Project managers interested in transitioning to managing Data Science projects
Curriculum
- Data Science Foundation - Introduction to Data Science, Industry applications, Terminologies
- Python Essentials for Data Science - Anaconda - Python distribution Installation and setup. Jupyter Notebook, Python Basics, Data structures, control statements.
- R Language Essentials - R Installation and Setup, R Studio Basics, R Data Structures, Control Statements, Data Science Packages.
- Maths for Data Science - Essential mathematics, Linear algebra, Linear Transformation, Types of Matrices, Matrix properties and Operations, Probability and Calculus.
- Statistics for Data Science - Run Down of Statistics, Terminologies, Inferential Statistics, Harnessing Data, Exploratory Analysis, Distributions, Central Limit Theorem, Hypothesis Testing, Correlation and Regression.
- Data Preparation with Pandas - Numpy Array functions, Data munging with Pandas, imputation, outlier analysis.
- Visualization with Python - Basics of Visualization, Matplotlib Introduction, Basic plots, customizing plots, Sub-plots, Statistical Plots, Seaborn package introduction.
- Machine Learning Associate - Machine Learning Introduction, ML core concepts, Unsupervised and Supervised Learning, Clustering with K-Means, Linear Regression, Logistic Regression, K-nearest Neighbor.
- Advanced Machine Learning - Bayes Theorem, Naïve Bayes Algorithm for text classification, Decision Tree, Ensemble methods: Random Forest, Extra Trees, SVM, Boosting Techniques, xgboost, Artificial Neural Network, Adv Metrics, Imbalanced Dataset, Grid search, K-fold Cross-validation
- SQL for Data Science - Relational Database Management Systems basics, SQL Introduction, Connection to SQL databases, Fetching data with SELECT, WHERE condition, SQL JOINs, SQL CRUD operations.
- Deep Learning - CNN Foundation - Deep Learning Introduction, TensorFlow and Keras, Convolution Neural Network basics, End to End image classification of cats and dogs using TensorFlow-Keras platform.
- Tableau Associate - Visual Analytics basics, Tableau Introduction, Connecting to the data source, dimensions vs measures, basic plots, compound plots, forecasting, publishing.
- ML Model Deploy - Flask API- ML Deployment Strategies, Flask introduction, Packing training ML model, Deploying it on Flask as API.
- Big Data Foundation - Introduction to Big Data, Hadoop Concepts, Spark Big Data for Data Science Processing. Handling Big Data in Machine Learning Pipeline.
- Data Science Project Execution - Data Science Project Management method, Business Case, Risk and Limitation of Machine Learning, Project Pitfalls.
Tools you will learn in Certified Data Scientist course
- The course provides excellent instruction in Data Science, making it a simple topic to learn about and a viable career option.
- Python, R, SAS, Apache Hadoop, Tableau, BigML, TensorFlow, Keras, SQL, Numpy, Knime, RapidMiner, Excel, Apache Flink, and Power BI are some of the primary Data Science tools covered in the Certified Data Scientist Course.
FAQs
Yes, you can pay the amount as EMI, we tied up with no cost EMI providers in the market
No, most of the software is free and open source. The guidelines to setup software are a part of course.
Certified Data Scientist is delivered in both Classroom and Online mode. Classroom is provided in selected cities in India such as Bangalore, Hyderabad.
Yes. The IABAC Exam fee is included in the course fee. No extra fee is charged.
All the online sessions are recorded and shared so you can revise the missed session. For Classroom, speak to the coordinator to join the session in another batch.