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Unbeatable 98% Placement Record

No doubt SOWC offers the best ai course in pune with 97.9% success rate.

64 hour+ Offline + Online Training

Both offline and online training options available as per your comfort.

Govt. Approved Masters Certificate

You will get Master in Artificial Intelligence Govt Approved Certificate

Live Projects With Industry Expert

Our expert will work with you personally on live projects!

1347+ Students, 99.5% Success rate!

Lokmanya House, forth floor. office 30, opposite kothrud police station, kothrud

(91) 8806799552

Relax. Discover. Gain New Real time insights of Artificial Intelligence!

Here's the snapshot of content details being covered in Master in Ai mentorship program by SOWC.

1. Introduction to AI

 

1. Definition, Scope,stages, applications,and effects of AI

2. Introduction to Data Science, Ai & ML

3. Use cases in business and& scope

4. Scientific Method & modeling concepts

5. CRISP-DM method basics of ML & DL

6. Supervised, semi-supervised & unsupervised learning

6. ML workflow & effective implementation

7. Performance Metrix

2. Statistics Essentials

 

1. Fundamentals Of Statistics, different types of data – Plot different types of data

2. Measures of central tendancy, Correlation & regression

3. Types of distribution, Confidence Intervals

4. Hypothesis formulationand testing, Data driven decisions

5. Regression Analysis, Understanding Variables

6. R essentials, R programming, commands & syntax,Packages & libraries

7.Introduction to Data Types,Data Structures in R

8.Importing, exporting data,Control structures & functions

9. Riptive statistics,Data Exploration, Qualitative & quantitative data

10. Measure of central tendancy, measure of positions, measure of dispersion & many other measures

3. Python for data science

 

1. Python Basics

2. Python Data Structures

3. Python Programming Fundamentals

4. Working with data in Python

5. Working in Numpy Arrays

4. Data Science Fundamentals

 

1. Intro DS: Data Science Intro and definition, Datafication, Big Data and Statistical Thinking

2. Data Preparation: About Data , Follow the Data

3. Tabular Data:  General concepts, Statistics, iterations and replications, Assignment

4. Data Cleaning and Integration 

5. Usage of Natural Language Processing

6. Exploratory Data Analysis

7. kNN, Linear Regression, k-Means

8. Naive Bayes, Logistic Regression, Trees and Forests

9. Scaling Up Analytics, Charles : MapReduce,” “Word Frequency Problem”, and “Other Examples of MapReduce”  framework

10. Visualization, Statistical Analysis

Initial Data Analysis

11. Relationship between attributes: Covariance, Correlation Coefficient, Chi Square

 12.Measure of Distribution (Skewness and Kurtosis), Box and Whisker Plot (Box Plot and its parts,

13. Using Box Plots to compare distribution) and other statistical graphs

14. Probability(Joint, marginal and conditional probabilities)

15. Probability distributions (Continuous and Discrete)

16. Density Functions and Cumulative functions

5. Machine Learning

 

1. Introduction to Artificial Intelligence and Machine Learning  , Data Wrangling and Manipulation   

2. Supervised Learning , Feature Engineering   

3. Supervised Learning-Classification ,Unsupervised learning   

4. Time Series Modelling , Ensemble Learning   

Recommender Systems   

5. Text Mining, Handling Text Data, Bag-of-words

6. Regular Expressions, Sentence Splitting and Tokenization

7.Punctuations and Stop words, Incorrect spellings

8. Properties of words and Word cloud, Lemmatization and Term-Document TxD computation

9.Sentiment Analysis (Case Study), Principles of Big Data

10. Introduction to Big Data, Challenges of processing Big Data (Volume, Velocity and Variety perspective), Use Cases

11. Big Data Frameworks – Hadoop, Spark and NoSQL, Processing, Storage andProgramming Framework, Hadoop eco-system Components and their functions

12. Essential Algorithms (Word count, Page Rank, IT-IDF), Spark: RDDs, Streaming and Spark ML , NoSQL concepts (CAP, ACID, NoSQL types)

6.Deep learning fundamentals

 

1 – Introduction to Deep Learning   

2 – Deep Learning Models   

3 – Additional Deep Learning Models   

4 – Deep Learning Platforms and Software Libraries   

5 – Auto-encoders and unsupervised learning

6. Stacked auto-encoders and semi-supervised learning

7. Regularization – Dropout and Batch normalization

7. Analytics Program management

1.Case Study 1: Churn Analysis and Prediction (Survival Modelling), Cox-proportional models

 2. Churn Prediction

Case Study 2: Credit card Fraud Analysis

 3.Imbalanced Data,Neural Network

Case study 3: Sentiment Analysis or Topic Mining from New York Times

 4.Similarity measures (Cosine Similarity, Chi-Square, N Grams)

 Part-of-Speech Tagging

 5. Stemming and Chunking

Case Study 4: Sales Funnel Analysis

 A/B testing

 6. Campaign effectiveness, Web page layout effectiveness

 Scoring and Ranking

7.Case Study 5: Recommendation Systems and Collaborative filtering

 User based

 Item Based

 8.Singular value decomposition–based recommenders

Case Study 6: Customer Segmentation and Value

 9.Segmentation Strategies

 Lifetime Value

Case Study 7: Portfolio Risk Conformance

 10. Risk Profiling

 Portfolio Optimization

Case Study 8: Uber Alternative Routing

11. Graph Construction

 Route Optimization

8. Forecasting Analytics

1. Data to Analytics to AI

 

2. ML Challenges

3. Internet of Things

4. Automated Machine Learning and Democratization of Insights

5. Real World Examples of Predictive & Prescriptive Analytics in AI

 

 

 

 

9. Data Visualization

1. Data Visualization using Tableau

2. Mastering Data Visualization using R

3. Word Clouds, Radar Charts & Waffle Charts

4. Creating Maps in R

5. Building interactive web pages

6. Creating and Customizing Shiny Apps

7. Additional Shiny Features

10. Big data technologies

1. The Melding of AI and Big Data

2. NLP, Computer vision & Robotics

3. General intelligence

4. Data Integration and Data Pipelines using Big Data Technologies

5. Model lifecycle management

6.Automation in data science with big data

7. Data preparation, data governance, and data lineage

8. Open Data, Data Generation and Data Networks

 

Studying artificial intelligence will open the world of opportunities to you. However, you need to keep in mind that you should not only learn but also thoroughly master ai in true sense. 

– School of wealth creation is best artificial intelligence (ai) training institute in Pune because we truly make our students the masters of the ai game. After completing the Masters In Artificial Intelligence at SOWC our students work as software engineers researching human machine interfaces, neural networks, quantum artificial intelligence.Some of our students also work as software engineers at big companies like Amazon, Google, Facebook analysing and processing the data. Some of our students also work as hardware engineers developing home assistants and robots.

– There are numerous opportunities you can tap into after finishing the Masters of Ai with us, so don’t wait. Call 9049574242 to know more or get demo with us.

– There are 2 types of artificial intelligence courses in the market. 1. Theoretical and Practical applications of Ai: This type of courses aim at teaching you theory and practical application. They also teach you how to build practical applications of AI. 

– Then there is type 2: Strategic applications of artificial intelligence. These type of courses aim at making you understand how ai can used in organizations to deliver real life value. 

– With 19+ years of experience our mentors give you best of both worlds. Our experienced expert mentors will not only teach you how to build practical applications of ai but also will teach you the real life implementation in organizations. We also charge lowest cost in the market so that money shouldn’t be the problem with the willing students. 

– These are the very reasons that make School of wealth creation the best artificial intelligence ( ai ) training institute in Pune and our masters in ai program the best artificial intelligence ( ai ) course in Pune. 

We have the deepest syllabus challenge. Ours is the best and most comprehensive syllabus with real life case studies and projects in the entire market. Please find the syllabus on the page details above. You can also watsapp 9049574242 to get the detailed brochure and syllabus. The best ai courses in pune is now affordable as well. Make most of our this month’s discount.

There are many institutes which charge in lacs for artificial intelligence courses and still don’t offer any placements assisstance. Here we offer 100% placement assistance which has resulted in all of our past students working for major conglomerates at top positions around the world,

There is absolutely zero technical background required for taking this life changing mentorship program. Anyone with strong desire to change his career and life can take this course and make it big in Ai world.

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