Executive Programme in Full Stack Data Science

The course will help participants prepare for (PMI-ACP)® exam. We impart the theoretical concepts of Agile Methodology to our students along with hands-on exercises. On completion of the PMI-ACP certificate training program, students can confidently lead large scale project teams in the capacity of an Agile coach.

Data Science project or IoT Project or Cloud Computing Project or Artificial Intelligence project, no matter which domain the project is from, we apply project management methodology. All the best practices of CAPM will be applied while doing the live projects.

• SQL, Which stands for Structured Query Language, is a language used for Relational Databases. RDBMS works on tables, which have a proper structure.
• Understanding on how to create tables to store the data & how to extract the specific information is relevant for any professional embarking on the journey of data analysis.
• Examples of SQL include Oracle, MySQL Server, PostgreSQL, sybase, etc.


• NoSQL, which is a Non-Relational Database Management System is used for Distributed Databases.it canhave a dynamic schema for unstructured data and can be stored, it can be column-oriented, document-oriented,graph-based or organized as a Key-Value pair.
• Understand how to leverage the capabilities of NoSQL alongside SQL, and increase the data management skills of professionals as well as students.
• Examples of NoSQL include:HBase, MongoDB, Elasticsearch, DocumentDB, Amazon DynamoDB, Bigtable, Cassandra,etc. 

Participants will be storing the data in relational database management system & will be able to query the data appropriately. Also participants will be able to store & retrieve the unstructured data from NoSQL databases such as MongoDB.

• Design independent IoT devices for sectors like Retail, Manufacturing and Construction
• Comprehend IoT architecture and Modern Microcontrollers for Data capture and Signal relaying
• Understand the advantages of Cloud storage
• Design and produce hardware compatible MCU
• Configure an HTTP server and develop python modules for basic Data Analytics
• Be able to understand IoT Communication Protocols

Participants shall be able to suggest on the best combination of IoT sensors suite so as to collect the data from the defined source & transport the data to cloud and/or on-premise infrastructure.

• Overview of Cloud and Types of services offered
• Ready for Certifications on AWS, Azure and GCP
• Ability to scale and deploy Cloud Infrastructure Services Independently
• Building Machine Learning Models on Cloud

Participants shall be able to make use of the majority of cloud components and migrate the data from existing on-premise environment to cloud environment via batch processing as well as real time streaming data flow.

• Work with various data generation sources
• Apply data-driven, Machine Learning approaches for business decisions
• Perform Text Mining to generate Customer Sentiment Analysis
• Build prediction models for day-to-day applicability
• Analyse Structured and Unstructured data using different tools and techniques
• Perform forecasting to take proactive business decisions
• Develop an understanding of Descriptive and Predictive Analytics
• Use Data Visualization concepts to represent data for easy understanding

Students will be able to perform predictive analytics on structured data. Use supervised and unsupervised learning techniques to derive insights on data for data driven decisions. Students will solve problems like identifying insider trading, cardiovascular risk detection models, crime rate predictions etc., by using cocktail models.

• Build AI systems using Deep Learning algorithms
• Process and analyse unstructured data such as images, videos and text
• Analyse sequence data and perform text analytics and Natural Language Processing using Recurrent Neural Networks
• Use various Python libraries such as Keras, TensorFlow and OpenCV to solve AI and Deep Learning problems
• Implement Deep Learning solutions and Image Processing applications using Convolution Neural Networks
• Apply graphical processing units in using Deep Learning algorithms

Students will be able to build classification models using Video & Image datasets, which includes behavioural analytics, autonomous vehicles, etc. Students will also be able to build AI-driven chatbot with both NLP capabilities as well as speech recognition capabilities.

• Install and set up Hadoop and Spark to store and process data
• Understand the advantages of distributed batch processing using HDFS
• Learn about Hadoop 1.x, 2.x and 3.x versions
• Perform exploratory queries on data batches using Pig, Hive and Spark
• Use Spark RDD optimisation techniques
• Write programmes in the Big Data domain as per system architecture

Students will be able to store big data using the Hadoop open source framework. They will be able to extract the data & process using Spark. Generate & publish reports using Tableau by establishing connection between Hadoop & Tableau.

• Get familiarised with Data Visualization principles and concepts
• Understand Tableau architecture, including the most important processes
• Data Generation and Data Collection
• Data Cleansing/Data Preparation
• Make exploratory Data Analysis using in-built options and default visualizations in Tableau
• Feature Engineering/Feature Engineering and Selection
• Data Visualization
• Conduct data extraction and data blending with multiple data sources
• Use Tableau filtering options, groups, sets and calculations, LOD expressions
• Create top charts in the latest version of Tableau Desktop
• Use Tableau calculated fields and advanced reporting concepts
• Create Tableau maps, dashboards and stories

Students will be directly connecting Tableau to various databases including streaming data. They will be using data blending by using multiple such data sources and generate meaningful dashboards & publish the same to stakeholders automatically.

Operations Research is applied on top of the regular predictive modelling performed using machine learning algorithms. This field predominantly includes two subjects of study - Data Optimization & Data Simulation. Data Optimization involves providing the best solution from the available pool of many solutions and most importantly when business constraints are levied on the problem at hand. Data Simulation is a technique used when data available is very limited and we want to artificially generate more data, given the small data. This is also used to perform what-if analysis so that managers may evaluate the various scenarios by changing the key parameters in a simulated environment. These two combined form the broad study of operations research.

Students will be working on projects, which includes the business problem, which involves finding the best solution given the business limitations or constraints. They will also be working on a project, which takes predictive models to the next level by providing provisions for decision makers to change the scenarios virtually & then take an action which best suits them.

With the emergence of data & with research organizations razor sharp focus on data generation, it is becoming extremely clear that data will be the guiding force for all the organizations. At the same time, miscreants getting their hands onto the precious data of organizations would mean loss of business & loss of reputation for companies. Hence securing the data via Data Security protocols, policies, procedures is imperative. Alongside understanding the difference between data security & data privacy will help organizations decide on what warrants to qualify data as PII or PHI so that one may uphold the protection of customer data. Securing the organization data as well as respecting the data privacy of customers are pivotal for success of organizations dealing with data.

There will be a simulated environment in which students have to don the hat of data security specialist & data privacy ninja. They will be scored based on the preventive as well as corrective measures taken to secure data to protect the customers data.

While understanding the generic data analysis techniques is very valid, even more valid will be to understand the finer nuances of the analytics performed in specific industries, sectors & domains. With analytics programs launched in the space of 56 different domains, 360DigiTMG commands a leader position in the education technology knowledge imparting segment. A few of the industry specific programs include Financial Analytics, Marketing Analytics, Supply Chain Analytics, Cyber Security Analytics, HR Analytics, etc.

Projects will be very focused based on the industry, sector or domain that students opt for. It could range from predicting employee sickness absence in HR analytics to capital asset pricing model in Financial analytics.