Create a design, methodology and framework for real life deployment & production using ML. At absolute Analytics we offer “Right mix of customization and generalization for reusability, allowing professionals to crossover within sectors by using our differentiator “7 Blocks for ML Implementation” through qualified and experienced professionals.

1. The assessment focuses in an optimized way the upstream design , methodology and approach part of large-scale analytics solution as well as downstream hands on implementation for zeroing on the entire analytics functions rather than only on theories.

2. Completely application-oriented hands on case study approach with real life sectorial focus in line with the industry requirement. It’s the best of the industry practioners way of gauging the readiness rather than the preachers’ point of view.

3. End to end focus on techniques , technologies , applications of converting ML outcomes to actions specific to the sector linking the data science key performance indicators (accuracy, F1 score, precision, recall , AUC) to business indicators (Profit, Revenue, Market share, Efficiency) helping to better understanding of the data science and business linkages for better placement ready in this stream.

4. Deep analysis of the performance across the consulting , implementation, technology and technique would help to gauge individually better in terms of the areas to be improved as well as an optimized roadmap for each candidate in line with their customized requirement would accentuate the optimized learning and career path.

5. The assessment in the data science space also ensures the seamless integration and linkages of functional knowledge including marketing, finance, operations, supply chain, HR with analytics thus gauging holistically at the macro level as well as in the micro specific areas.

Create a design, methodology and framework for real life deployment & production using ML. At absolute Analytics we offer “Right mix of customization and generalization for reusability, allowing professionals to crossover within sectors by using our differentiator “7 Blocks for ML Implementation” through qualified and experienced professionals.

1. The assessment focuses in an optimized way the upstream design , methodology and approach part of large-scale analytics solution as well as downstream hands on implementation for zeroing on the entire analytics functions rather than only on theories.

2. Completely application-oriented hands on case study approach with real life sectorial focus in line with the industry requirement. It’s the best of the industry practioners way of gauging the readiness rather than the preachers’ point of view.

3. End to end focus on techniques , technologies , applications of converting ML outcomes to actions specific to the sector linking the data science key performance indicators (accuracy, F1 score, precision, recall , AUC) to business indicators (Profit, Revenue, Market share, Efficiency) helping to better understanding of the data science and business linkages for better placement ready in this stream.

4. Deep analysis of the performance across the consulting , implementation, technology and technique would help to gauge individually better in terms of the areas to be improved as well as an optimized roadmap for each candidate in line with their customized requirement would accentuate the optimized learning and career path.

5. The assessment in the data science space also ensures the seamless integration and linkages of functional knowledge including marketing, finance, operations, supply chain, HR with analytics thus gauging holistically at the macro level as well as in the micro specific areas.

Certification in Data Science

Description

• 200 Hours of Training delivered through live webinar sessions
• Course coverage in R, SAS, Python and Tableau in the technology dimensions
• Learning includes deep rooted sectorial pain points and their customized solutions
• Live Project coverage by certified industry professionals
• Focus across entire Data Analytics Landscape

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