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

Brijesh Nair

PgMP certified on 26th October 2018. "Addon Skills" is highly professional training institute & they really have a structured methodological approach of course delivery, which facilitates each & every participant to achieve the goal & objective of PgMP Certification in short span of time (2-3 months) successfully. Training Program helps to develop deep understanding & greater Insights of the Program Management Concepts, provide reference to SPM v4 & ECO Clauses, Practical Case Studies & Examples, Mock Tests, Post training support sessions, Application Writing Sessions, etc. Regular feedback sessions to ensure the candidate has really understood & absorbed the concept explained is the essence of the training program. Kailash is strongly determined, dedicated & devoted to his job of delivering the training to the best possible extent. Regular follow-ups by Addon Skills on the overall progress of learning of candidate & pushing the candidates to take the extra mile in their busy schedule is really appreciated!! The 'Live Chat Service' on WhatsApp for clarification of doubts answered by expert trainers instantaneously is exemplary service offered!! Last but not the least, it’s worth enrolling for the training program!!

Shubham Maurya

asdsad

Dr. Chandramouli Subramanian

Attended Pfmp training by Addon skills, Mr. Kailash in the month of Oct 2020. it was a wonderful experience refreshing PPP concepts. He is passionate about explaining all doubts in detail. value delivered clearly aligned with the stated and unstated goals. He reinforced all important points. His tips on how to fill application was a value Added: He took the entire training concisely. I recommend this to all portfolio managers.

Jeeva Iyer

Excellent trainer for PMP and PMI related certifications. Very practical approach and exam oriented as well.

Muzaffar Sheikh

PMP training with Kailash was an amazing journey as he is very knowledgeable and has an excellent approach to explaining content with good examples.

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