Organisations across industries and geographies are entering the era of Artificial Intelligence (AI) today.  AI will redefine businesses and careers.

Must-have Skills

  • Knowledge of statistics, probability, predictions, calculus, algebra, Bayesian algorithms
  • Applicable knowledge in data structures, logic and efficiency, programming languages like Python
  • Understanding of data services like Blockchain

IBM AI / ML Course

A structured learning course designed by industry experts offering:

  • Essential skills in programming languages like C/C++, Java Fundamentals, Python
  • Proficiency in Data Visualisation and Text Analytics
  • In depth knowledge in Business Intelligence and Predictive Modelling
  • Development of Machine Learning Models (Watson Studio)
  • Structured learning and use of AI services

Real Life Use Cases of AI / ML

AI-backed data analytics: Leveraging real-time analytics on a wide variety of data to deliver personalisation, identify the right product offers and pricing, and build customer relationships.

Cybersecurity: Analysing security information to detect frauds, identify vulnerabilities, protect data and assets, and improve security operations and response.

Organisational data: Gaining insights from organizational data for sales/revenue forecasting, operations management, energy and cost optimisation, real-time business intelligence and more.

Business functions: Application of AI across functional areas such as customer support (natural language processing), manufacturing (robots), finance, IT management, HR (recruiting automation).

Industry transformation: Driving intelligence-led innovation in industries as varied as automotive, biosciences, education, healthcare, smart cities, financial services, travel, retail and more.

Career Avenues

Machine Learning Engineer
Role: Develop ML systems, run learning tests and experiments, and deploy ML algorithms
Competence: Python, R, Natural Language Processing, statistics, applied mathematics, and tools such as IntelliJ and Eclipse

Data Scientist
Role: Capture, process and interpret data for insights using ML models, predictive analytics and AI
Competence: Working with data sets, thorough knowledge of Python, R

Business Intelligence Developer
Role: Develop, deploy and maintain BI interfaces including query tools and interactive dashboards
Competence: DB/DBA and data analysis, software engineering and business analytics 

Big Data Engineer/Architect
Role: Create database solutions, deploy information systems and analyse structural requirements
Competence: Database structure principles, analytical skills

Data Analyst
Role: Collect, interpret and analyse data about specific topics and report the findings
Competence: Mathematics, statistics, spreadsheets, data visualisation tools, Python


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