What you get from this programme

  • In-demand
    skillset

    Master Data Visualization, Exploratory Data Analysis, Artificial Intelligence & Neural Networks and implement Big Data techniques (using tools like R, Excel, Tableau, SQL, NoSQL, Hadoop, and more) to deploy enterprise information management & solve business problems.

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  • Mastery in emerging
    technologies

    Become proficient in AI, ML & Neural Network that emphasize the creation of intelligent machines.

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  • Hands-on
    Experience

    Get hands-on learning experience in Data Science labs that are equipped with the latest analytics software & applications that will make you thorough with the core concepts of the programme.

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  • Guaranteed
    placement

    Get a 100% guaranteed placement* after successfully completing the programme.

    READ MORE

In-demand
skillset

Master Data Visualization, Exploratory Data Analysis, Artificial Intelligence & Neural Networks and implement Big Data techniques (using tools like R, Excel, Tableau, SQL, NoSQL, Hadoop, and more) to deploy enterprise information management & solve business problems.

Mastery in emerging
technologies

Become proficient in AI, ML & Neural Network that emphasize the creation of intelligent machines.

Hands-on
Experience

Get hands-on learning experience in Data Science labs that are equipped with the latest analytics software & applications that will make you thorough with the core concepts of the programme.

Guaranteed
placement

Get a 100% guaranteed placement* after successfully completing the programme.

Tools

Programme curriculum

Programming for Data Science

  • Basics of Python
  • Python core data structures
  • Functions & modules
  • Object-oriented programming
  • Structured exception handling
  • FILE input/output
  • NumPy and Panda

Statistical techniques for data science

  • Introduction to statistics
  • Probability
  • Sampling
  • Testing of hypothesis
  • Data relationship through correlation
  • Regression

Data scrapping and data wrangling

  • Data scrapping
  • Types of data, finding data across sources
  • Querying an API directly - stocks, weathers etc.
  • Browser-based scrapping
  • Scrapping tables such as Wikipedia/IMDB
  • Data wrangling
  • Data quality detection
  • Integrating data from multiple sources
  • Transforming data
  • Pivoting & aggregation and joining
  • Introduction to database management systems

Data analysis and visualization

  • Data Analysis and storytelling
  • Visualization and communication using descriptive analysis
  • Data cleansing and transformation, building dashboards
  • Dimension reduction and visualization

Big Data technologies

  • Motivation for Big Data
  • Hadoop components
  • Understanding HBase
  • Analysing data with Hive and Pig
  • Sqoop, Flume and Kafka
  • Understanding Spark
  • Spark programming

Machine
Learning

  • Introduction to Machine Learning and Data Science
  • Classification
  • Validation measures
  • Clustering
  • Recommendation systems
  • Customer analytics
  • Time series

Artificial Intelligence

  • Introduction to AI
  • Applications of AI
  • Programming with TensorFlow
  • High-level TensorFlow APIs
  • TensorBoard
  • Deep Learning (DL) and reinforcement learning

Success statistics

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Average percentage of salary hikes received by Jigsaw students

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Interviews scheduled for Jigsaw students in 2019

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Highest salary earned by a Jigsaw alum with less than 3 years of experience

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Job postings on the Jigsaw career board in 2019

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Jigsaw students who have successfully moved to a career in data science

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Number of companies that hire Jigsaw graduates
Meet our faculty
  • Gaurav Vohra

    Faculty, CEO & Co-founder, Jigsaw Academy

    Gaurav has over 18 years of experience in the field of analytics and has worked across multiple verticals including financial services, retail, FMCG, telecom, pharmaceuticals, and leisure industries.

  • Sarita Digumarti

    Faculty, Co-founder, Jigsaw Academy

    Sarita has more than 18 years of extensive analytics and consulting experience across diverse domains including retail, healthcare, and financial services. Her focus as an educator is on offering quality education in analytics, backed by application-oriented learning & training.

  • R.N. Prasad

    Faculty, BE (Electrical Engg.)

    R.N. Prasad is a trusted advisor for Analytics and Product Management, and has been helping companies develop innovative BI, Analytics and Data Science applications. A Harvard-certified instructor and a Franklin Covey certified 4DX coach, Prasad loves to share his passion for technology in the classrooms.

  • Dr. Gangaboraiah

    Faculty, M.Sc. (Statistics), Ph.D. (Statistics)

Alumni speak

  • Venkata Ravindranath

    Consultant, Fractal Analytics

    "As a JS Developer, I was making a modest salary in a stagnant role & I wasn’t excited about my growth prospects. With this Data Science PG Diploma, I got that crucial upgrade as a Data Consultant, with an 86% pay hike!"

  • Sreshta Sinha Roy

    Research Analyst, Amazon

    "Even with a BE in E&C, I knew that I needed a specialization to make a mark. I opted for an online course & soon realised it won’t be enough. But this Data Science Diploma with hackathons, datathons & industry interactions truly gave me my edge. And today, I’m with Amazon."

  • Halappa Guruppanavar

    Business Analyst, TCS

    "As a BBM graduate, I had almost accepted that I can never make it into analytics, because of my lack of relevant education. But this Data Science program didn’t just bring me my dream job but also a salary hike of 110%."

How Jigsaw Academy helps you build your career

Step 1
TRAINING AND RESUME PREPARATION
Step 2
LIVE PROJECTS AND INDUSTRY EXPERIENCE
Step 3
INTERVIEW
PREPARATION
Step 4
COMPANY
CONNECT

Questions you might have

What is the placement guarantee??

Every learner who successfully completes the academic requirements of the Postgraduate Diploma in Data Science from Manipal Academy of Higher Education (MAHE) and adheres to the placement criteria will get three placement opportunities that Jigsaw Academy will arrange with the hiring companies. In case they do not get placed by the end of the program, they will receive a stipend of INR 20,000 for the next three months.

What are the eligibility criteria for the Guaranteed Placement?

The Guaranteed Placement criteria are:

- A learner must have at least 50% marks in their graduation programme

- They should meet the minimum standards for attendance

- They should also match the minimum assessment criteria (academic performance and placement interventions)

What happens if I meet the Guaranteed Placement criteria but don’t get the 3 placement opportunities promised to me by the end of the course?

If any learner fulfills the Guaranteed placement criteria but doesn’t receive the 3 placement opportunities by the end of the 11-month program, they will receive a stipend of INR 20,000 per month for the next 3 months.

However, the following learners are not eligible for a stipend of INR 20,000 per month for the next 3 months:

- Those who have graduated 3+ years before joining the course

- Learners who have taken a year off work or academics before joining the program