CERTIFIED DATA SCIENTIST COURSE

• Introduction To Data Science
• Industry Applications
• Terminologies

• Anaconda - Python Distribution Installation And Setup
• Jupyter Notebook
• Python Basics
• Data Structures
• Control Statements

• R Installation And Setup
• R Studio Basics
• R Data Structures
• Control Statements
• Data Science Packages

• Essential Mathematics
• Linear Algebra
• Linear Transformation
• Types Of Matrices, Matrix Properties, And Operations Probability And Calculus

• Statistics Introduction
• Terminologies
• Inferential Statistics
• Harnessing Data
• Exploratory Analysis
• Distributions
• Central Limit Theorem
• Hypothesis Testing
• Correlation, And Regression

• Numpy Array Functions
• Data Munging With Pandas
• Imputation
• Outlier Analysis

• Visualization Basics
• Matplotlib Introduction
• Basic Plots
• Customizing Plots
• Sub-Plots
• Statistical Plots
• Seaborn Package Introduction

• Machine Learning Introduction
• Ml Core Concepts
• Unsupervised And Supervised Learning
• Clustering With K-Means
• Linear Regression
• Logistic Regression
• K-Nearest Neighbor

• 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

• Relational Database Management Systems Basics
• Sql Introduction
• Connection To Sql Databases
• Fetching Data With Select
• Where Condition
• Sql Joins
• Sql Crud Operations

• Deep Learning Introduction
• Tensorflow And Keras
• Convolution Neural Network Basics
• End To End Image Classification Of Cats And Dogs Using The Tensorflow-Keras Platform.

• Visual Analytics Basics
• Tableau Introduction
• Connecting To Datasource
• Dimensions Vs Measures
• Basic Plots
• Compound Plots
• Forecasting
• Publishing

• Ml Deployment Strategies
• Flask Introduction
• Packing Training Ml Model
• Deploying It On Flask As Api

• Data Science Project Management Method
• Business Case Risk
• Limitation Of Machine Learning
• Project Pitfalls.

Introduction to Big Data

• Hadoop Concepts
• Spark Big Data for Data Science Processing
• Handling Big Data in Machine Learning Pipeline.

DataMites™ Certified Data scientist is designed to provide a right blend of all four facets of Data Science

• These four facets form four pillars for the data science field. They are 1. Programing 2. Statistics 3. Machine Learning 4. Business Knowledge.
• The course is mainly focussed on Python for core data science programming, it also includes R as necessary to enable professionals working in R.
• Statistics are covered as required for a Data Scientist, you may find a detailed syllabus in syllabus tab.
• Machine Learning is the main tool kit for Data Science in predicting classification or regression.
• This course courses all popular ML algorithms as detailed in the syllabus tab.
• This course allows candidates to obtain an in-depth knowledge by laying a strong foundation and covering all the latest data science topics.
• The increasing demand curve for data science professionals to manage the large set of data in various organizations providing millions of job opportunities in global markets.
• The knowledge gained through this course along with IABAC™ certificate surely helps you to become a data science professional.

This course comes as a perfect package of required Data Science skills including programming , statistics and Machine Learning. If you aspire to be Data Science professionals, this course can immensely help you to reach your goal.

After successful completion of this “Certified Data scientist” course, you should have

• Gained a better knowledge of the entire Data Science project workflow.
• Understand key concepts of statistics
• Gained hands-on knowledge of popular Machine learning algorithms
• In depth knowledge on Data Mining, Data forecasting, and Data Visualization.
• Able to create business case for Data Science project
• Deliver end to end data science project to customer

Data science is the hottest field in the market as on today. Be it a small company or an MNC, they need a Data scientist to manage their large pool of data.

• High demand for data scientists with only a few qualified people to hire
• High salaries, nearly twice of an average software engineer as per Glassdoor report
• This course not only designed to enable you for new career opportunities but also allows you to apply the new-age skills in your current work and become valuable in your current role.
• Be assured that you are entering the future of data science much earlier to grab those wonderful opportunities arising from this biggest need in the business world.

This course “Certified Data scientist” is not restricted to any specific domain.

• Fresh Graduates or students from any discipline can choose this course to obtain better job opportunities in this most demanding data science field
• Working professionals looking to change their domain to data science field.
• Highly recommended for those who are aspiring jobs that mainly revolves around data analytics and machine learning
• Project managers aspiring to switch to manage Data Science projects

DataMites™ is the global institute for Data Science accredited by International Association of Business Analytics Certifications (IABAC). DataMites provides flexible learning options from Classroom training, Live Online to high quality recorded sessions

The 6 Key reasons to choose Data Mites™

IABAC™ Accredited

• Globally reputed certification
• Syllabus Aligned with IABAC global market standards

Elite Faculty & Mentors

• Best in industry faculty from IIMs
• Course structured by Professors in Data Science from top universities
• Ensures high quality learning experience

Learning Approach

• Learning through case study approach
• Theory → Hands On → Case Study → Project → Model Deployment

10+ Industry Projects

• 10+ Industry related projects
• Enabling candidates to gain real time skills, also boosting confidence for real challenges

PAT (Placement Assistance Team)

• Dedicated PAT (Placement assistanceTeam)
• Resume assist service
• Mapping candidates to verified jobs by PAT team
• Supporting in Interview preparation

24x7 Cloud Lab for ONE year

• High capacity data science cloud lab
• All Machine Learning python and R scripts on cloud lab for quick reference
• Enable participants to practice Data Science even with their mobile phones through cloud lab

Total course fee should be paid before 50% of the course completion. We also have EMI option tied up with bank. Check with coordinators.

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.

We have a dedicated PAT (Placement Assistance team) to provide 100% support in finding your dream job.

The DataMites Placement Assistance Team(PAT) facilitates the aspirants in taking all the necessary steps in starting their career in Data Science. Some of the services provided by PAT are: -

• 1. Job connect
• 2. Resume Building
• 3. Mock interview with industry experts
• 4. Interview questions

The DataMites Placement Assistance Team(PAT) conducts sessions on career mentoring for the aspirants with a view of helping them realize the purpose they have to serve when they step into the corporate world. The students are guided by industry experts about the various possibilities in the Data Science career, this will help the aspirants to draw a clear picture of the career options available. Also, they will be made knowledgeable about the various obstacles they are likely to face as a fresher in the field, and how they can tackle.

No, PAT does not promise a job, but it helps the aspirants to build the required potential needed in landing a career. The aspirants can capitalize on the acquired skills, in the long run, to a successful career in Data Science.