data-science-bootcamp

Data Science Bootcamp

OUR ALUMNAE

Ashish Shah PfMP results
Ashish Shah PfMP results
Ashish Shah PfMP results
Ashish Shah PfMP results
Ashish Shah PfMP results
Ashish Shah PfMP results
Ashish Shah PfMP results
Ashish Shah PfMP results
Ashish Shah PfMP results
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DESCRIPTION

Level I - In this program students are taught Math, Stats, and basic Programming skills to bring all to same level.

Level II – Students undergo beginner and intermediate level of training on R, Python, and Data Visualization. A project work using each of these technologies through Polyglot approach.

Level III – Students undergo high level of training on Data Mining concepts, and Statistical Modelling.

Level IV – A thorough and detailed study of Machine Learning concepts and models using both R & Python simultaneously, again using Polyglot approach.

Level V - Hadoop, Spark, NoSQL, Kafka, Pig, Hive, Sqoop, Flume.

Level VI – Project work. A student can work on 5 projects which will be reviewed by peers, and industry experts.

Data Science in 24 weeks classroom training

Exhaustive and strategic training coordinated with continuously evolving statistical & data modelling techniques.

A comprehensive curriculum

It teaches Maths, Stats, R, Python, ML, Hadoop, Spark & many more. 

Continuous upgradation

Curriculum is continuously updated and drawn from engagement with industr y consultations and partnerships. 

A portfolio of real world projects

Each one gets to create a personal portfolio of multiple projects.

Create online profile for industry

  • Participate in Kaggle competitions.
  • Create own Github account and repository.

Career assistance

Get personalised assistance through soft skills, mock interviews, networking, and interview calls.

Access to free resources

  • Get access to repository of books, white papers.
  • Free access to Data camp for brushing up R & Python.
[Math & Stats] Week 1, 2 & 3 : Statistics, Probability, Linear Algebra - Vectors, Matrix, Calculus, Derivatives, Integration, Limits, Log, and Trigonometry. Basics of algorithm and data structures. Introduction to Linux, Git, Kaggle. Level I.

[R] Week 4 & 5 : Learning R – Installing R studio, programming basics, features, data types, vectors, matrices, controls, loops, functions, packages, importing data, visualization, packages . Level II. Project due.

[Python] Week 6 & 7 : Learning Python – Installing Anaconda, programming basics, data types, list, tuples, dictionary, controls, loops, Numpy, Pandas, functions, importing & scraping data, and visualization. Level II. Project due.

[Data Mining, Statistical Modelling] Week 8 & 9 : Data types, pre-processing, data warehousing, Regression, Supervised & Unsupervised patterns & mining, classification – trees, Bayes, backpropagation, SVM, KNN, Rough set, Fuzzy set, Clustering – K-means, Kmedoids. Outlier detection – Statistical methods, Proximity based methods, and clustering methods. Level III. Written exam due.

[Data Science (Machine Learning) with R] Week 10 & 11 : Installing packages, datasets, foundation of statistics in R, missingness & imputations, Supervised Learning – regressions (Simple & multiple regressions), generalized regression, classifications (KNN, Decision Tree, Random Forest, Bagging & Boosting, SVM, Pruning/ GINI/Entropy), Feature Engineering / Preprocessing, Unsupervised Learning / Clustering – K-means, Hierarchical, Agglomerative), Dimensionality handling – Rigde & Lasso regression, Cross Validation, Bias/Variance Tradeoff, Principal Component Analysis. Level IV.
Project due

[Natural Language Processing with R] Week 12 : Introduction to NLP, corpus, stemming & chunking, Naïve Bayes, Association rule, Text classification, Case studies. Level IV. Project due

[Data Science (Machine Learning) with Python] Week 13 & 14 : Scikit learn, Stats module, Simple & multiple linear regression, Classification – Logistic regression, discriminant analysis, Naïve Bayes, SVM, decision Tree, Random Forest; Model Selection – Cross Validation, Bootstrap, Feature selection, Regularization, Grid search; Unsupervised Learning – Principal Component Analysis, Kmeans and Hierarchical clustering. Level IV. Project due.

[Big Data – Hadoop, Spark, Kafka, Pig, Sqoop, Flume & tools] Week 15 & 16 : Hadoop, HDFS, Mapreduce, Apache Hive, Spark, Spark MLib. Level V. Project due

[Deep Learning using TensorFlow] Week 17 : TensorFlow using Python. Level V. Project due.

[Overview – Tableau, IoT, Cloud, Excel, Timeseries] Week 18 : Hands-on Tableau for visualization, Introduction to IoT & Cloud, Study on Timeseries using R. Level V.

[Projects] Weeks 19 to 24 : Retail Analytics, HR Analytics, Market Research, Text Analytics and one project of choice (Recommender Engine, Disaster monitoring through social media, Skin Cancer image processing, Sentiment / News Analysis). Level VI.

Interview preparation :

  • Online profile creation & improvement – Github, Kaggle, LinkedIn 
  • Resume review and updating as per industry needs
  • Soft skill sessions for personality development & grooming 
  • Mock interviews and workshops

1st round : We will arrange 3 interviews with organizations working on analytics. 

2nd round : Those unsuccessful in 1st round, will be placed in our sister concern / partner companies with stipend for 3 months.

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Our Testimonials

Rohit Kapoor

I attended certification training from the Addonskills. Very much pleased with the professionalism, dedication, and timely help from the team. The direction and study material shared by Addonskills really helped me to grasp the concept on the fast track and saved a lot of time for me. One to one interaction with the mentor on doubts made me comfortable for the exam and real-world challenges. I highly recommend Addonskills for all kind of project management training and advisory/consulting services for the corporate.

Jyothi Parampalli

Happy to have earned Program Management Professional (PgMP) Certification in my maiden attempt and all credit goes to Addon Skills! I was a student of AddonSkills from 4th Nov '17 and the coaching provided by them gave me enough confidence to appear and clear the exam within two months i.e. on 8th Jan '18. The study materials, question banks & joint session to solve them, sessions around ECO and additional Q&A discussions in the WhatsApp group all contributed towards getting my Program Management concepts strong. The examples were relevant and provided right insight into understanding the scenarios to apply program management best practices.

Raviraj Mundhe

Thank you Addon Skills. Your training programme and training material/notes were very useful and helped me prepare and pass the exam. The support system even after the training is what helps aspirants focus their strategies. Thank you very much for your mentoring support and wish the entire team good luck with the certification training workshops.

Rahul Sontake

Addon Skills, you has been instrumental in my PgMP certification success. I was able to clear the exam within 45 days from attending this training. Beyond the three days session, your personal involvement & engagement individually, is a key differentiator which has helped in expediting the certification completion. Engaging with AddON Skills have been very fruitful.

Akhil Sharma

I have attained the PgMP preparation training course from Addon Skills and found it very useful and extremely good learning experience. Trainer has enriched knowledge on PMI fundamentals and beauty of training is that, they mainly focus on the basic fundamentals & make the entire training so valuable by sharing enrich experience and mapping it towards Program Management Standards. I have gone through many trainings in my professional carrier, but I will not hesitate to say that he is one of the best training I have ever attended in my life which has also helped me attained PgMP certification. Thanks, Akhil

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