India’s Analytics, Data Science and Big Data industry is currently pegged at $2.71 billion annually in revenues, growing at a consistent rate of 33.5% (CAGR), and market leaders are heavily investing in data science in various sectors such as Telecommunication, Healthcare, Fintech, IT, etc. PWC estimates that year 2020 will see about 2.7 million job postings for data science and analytics role.
The scope of Data Science roles is growing at a fast pace and every aspect of businesses is trying to leverage the huge amounts of data that is currently been generated. Variety of job opportunities related to data are coming up for people from varied background.
Intel is an American multinational corporation headquartered in Santa Clara, California, in the Silicon Valley. The brand works with ecosystem partners to provide technologies that power a comprehensive, advanced analytics solution, from providing big data infrastructure to contributing to open-source projects. Intel’s strategy is to help ensure that every data scientist, developer and practitioner has access to the best platform and easiest starting point to solve the Artificial Intelligence (AI) problem being tackled from the data center to the edge.
In association with Intel Corporation, one of the leading global technology giants as knowledge partner, TIMES TSW’s objective is to reduce the supply-demand gap by creating equipped and expert data scientists & AI experts out of young professionals.
The program is crafted to prepare you for a Data Science role in the industry. The blended mode of program gives you flexibility to learn at your own pace while at the same time the weekly online mentoring sessions will always assure that you are on your toes learning new things every week. The curriculum has been designed with our industry partners and you will have a regular interaction with industry practitioners through workshops, industry sessions and hackathons.
Module 1: Foundation Courses for Data Science
- Understanding Data Science
- Introduction to Programming with Python
- Foundations of Linear Algebra
- Foundations of Statistics
Module 2: Python for Data Science
- Getting Started with Python Programming
- Hands-on Linear Algebra with NumPy
- Data Pre-Processing using Pandas
- Basic Data Visualization using Matplotlib
Module 3: Statistical Thinking for Data Science
- Descriptive Statistics
- Essential Concepts in Probability
- Probability Distributions
- Inferential Statistics
Module 4: Exploratory Data Analysis and Data Visualization
- Sourcing data from different sourcess
- Data Wranglings
- Working with Databases (SQL Primer)s
- Designing your own data for business problems
- Exploratory Data Analysiss
- Data Visualization using Tableaus
Module 5: Big Data
- Why Big Data?
- Hadoop as a solution to Big Data
- Hadoop Ecosystem
- HDFS, Map Reduce, YARN, Apache HIVE
- Apache Spark
Module 6: Machine Learning Techniques
- Introduction to Machine Learning
- Linear Regression
- k Nearest Neighbours
- Logistic Regression
- Support Vector Machines
- Unsupervised Learning using Clustering
- Decision Trees
Module 7: Advanced Machine Learning Techniques
- Bias and Variance
- Overfitting and Regularization
- Ensemble Methods in Machine Learning
- Gradient Boosting Machines
- Feature Engineering and Feature Selection Techniques
- Special Cases in Machine Learning
- Working with Time Series Data
- Time Series Forecasting
Module 8: Text Analytics
- Introduction to Text Data & Analytics
- Pre Processing Text Data
- Sentiment Analysis on Text Data
- Document Summarization
- Topic Modelling
Module 9: Programming with TensorFlow
- Programming with TensorFlow
- What is new with TensorFlow 2.0
Module 10: Foundations of Neural Network
- Introduction to Perceptron
- Perceptron training
- Deep Neural Networks
Module 11: Deep Learning
- Image Recognition using CNN
- Speech Recognition using RNN
Module 12: Career Preparation
- Building Effective Resume
- Getting noticed on LinkedIn
- Mock Interviews
- Domain based case studies
- Online classroom teaching by industry experts with hands-on real-time training
- Weekend curriculum schedule to minimise disruption for working professionals
- Individual and group assignments, discussions and feedback
- Access to INTEL project data sets | INTEL hardware platforms through Jupyter notebooks.
- Participate in INTEL Hackathons, webinars and seminars by industry experts.
- Hands on experience in multiple domains such as Healthcare, BFSI, Retail, Telecom, IT, etc.
- 50 hours of GPU environment
- Industry Capstone projects
- Experts from Flipkart, Fractal Analytics, Walmart, etc
Who Should Apply
- Working professionals/Freshers with an analytic bent of mind and superlative academic credentials with an Engineering background
Eligibility and Admission Criteria
- Professionals with minimum 2 years of experience possessing a Bachelor’s / Master’s Degree in Science / Engineering / Mathematics / Statistics / Economics (OR)
- An equivalent qualification (with Mathematics / Statistics as one of the subjects)
- Successful Clearance of Admission Test and Personal Interview
- 6-months , 24 weekends, 200+ hours
- 60 hours content + 80 hours hands on activities
- 80+ hours online instructor led mentoring
Assessment and Certification
Assessment is carried out by the faculty through:
- Mini Projects
- Capstone project
- Coding Workshop
The participant earns a certificate of completion/participation from Intel & Times TSW upon successful completion of the course.
Lab & Hands on Exercises
- 80 hours of hands-on activities.
- Capstone project to create a usable/public data product that can be used to show your skills to potential employers. Live project’s with corporate partner with mini-project electives from various industries (IT, Retail, BFSI, Healthcare and telecom).
- Resume Preparation & Job Assistance – Mentoring by experts to help you choose the right project that will add weightage to your resume. Placement Assistance by a team of dedicated specialists to help place you in the right job within the right industry.
- Join the ranks of a strong alumni network of Times Professional Learning and Leverage the corporate network of the Times Group for career and placement services.
- Our participants are currently employed by: PwC, WNS, Cognizant, Wipro, HSBC, TCS, etc.