- 4 months program with 200+ learning hours
- 1 Client/live project with internship experience certificate
- No-code course, Excel, MySQL, Tableau & Power BI
DATA ANALYTICS LEAD MENTOR
Amin Ali
A globally reputed Data Analytics Expert with 19 years experience in Analytics and Data Science. Trained over 05k Data Science aspirants , currently serving as Founder and CEO at Softosmith, an Software Development ML/AI company. Amin Ali holds MSc Economics and Software Engineering, Data Science, Google, IBM and Microsoft Certifications. He is MPhil Scholar.
ABOUT CERTIFIED DATA ANALYST COURSE
Phase 1
Phase 3
Students participate in a 2-month internship and project with specialised supervision from professionals. This phase involves experience certification, 10 capstone projects, and 1 live/client project.
Phase 2
Phase 4
Students participate in a 2-month internship and project with specialised supervision from professionals. This phase involves experience certification, 10 capstone projects, and 1 live/client project.
Certified Data Analyst Learning Plan
MODULE 1: DATA ANALYSIS FOUNDATION
MODULE 2: CLASSIFICATION OF ANALYTICS
MODULE 3: CRIP-DM Model
MODULE 4: UNIVARIATE DATA ANALYSIS
MODULE 5: DATA ANALYSIS WITH VISUAL CHARTS
MODULE 6: BI-VARIATE DATA ANALYSIS
MODULE 1: PYTHON BASICS
MODULE 2: PYTHON CONTROL STATEMENTS
MODULE 3: PYTHON DATA STRUCTURES
MODULE 4: PYTHON FUNCTIONS
MODULE 5: PYTHON NUMPY PACKAGE
MODULE 6: PYTHON PANDAS PACKAGE
MODULE 1: DATA SCIENCE ESSENTIALS
MODULE 2: DATA ENGINEERING FOUNDATION
MODULE 3: PYTHON FOR DATA ANALYSIS
MODULE 4: VISUALIZATION WITH PYTHON
MODULE 5: STATISTICS
MODULE 6: MACHINE LEARNING INTRODUCTION
MODULE 1: COMPARISION AND CORRELATION ANALYSIS
MODULE 2: VARIANCE AND FREQUENCY ANALYSIS
MODULE 3: RANKING ANALYSIS
MODULE 4: BREAK EVEN ANALYSIS
MODULE 5: PARETO (80/20 RULE) ANALSYSIS
MODULE 6: Time Series and Trend Analysis
MODULE 7: DATA ANALYSIS BUSINESS REPORTING
MODULE 1: DATA ANALYTICS FOUNDATION
MODULE 2: OPTIMIZATION MODELS
MODULE 3: PREDICTIVE ANALYTICS WITH REGRESSION
MODULE 4: DECISION MODELING
MODULE 1: MACHINE LEARNING INTRODUCTION
MODULE 2: ML ALGO: LINEAR REGRESSSION
MODULE 3: ML ALGO: LOGISTIC REGRESSION
MODULE 4: ML ALGO: KNN
MODULE 5: ML ALGO: K MEANS CLUSTERING
MODULE 6: ML ALGO: DECISION TREE
MODULE 7: ML ALGO: SUPPORT VECTOR MACHINE (SVM)
MODULE 8: ARTIFICIAL NEURAL NETWORK (ANN)
MODULE 9: PROJECT: PREDICTIVE ANALYTICS WITH ML
MODULE 1: GIT INTRODUCTION
MODULE 2: GIT REPOSITORY and GitHub
MODULE 3: COMMITS, PULL, FETCH AND PUSH
MODULE 4: TAGGING, BRANCHING AND MERGING
MODULE 5: UNDOING CHANGES
MODULE 6: GIT WITH GITHUB AND BITBUCKET
MODULE 1: DATA ANALYSIS FOUNDATION
MODULE 2: CLASSIFICATION OF ANALYTICS
MODULE 3: CRIP-DM Model
MODULE 4: UNIVARIATE DATA ANALYSIS
MODULE 5: DATA ANALYSIS WITH VISUAL CHARTS
MODULE 6: BI-VARIATE DATA ANALYSIS
MODULE 1: PYTHON BASICS
MODULE 2: PYTHON CONTROL STATEMENTS
MODULE 3: PYTHON DATA STRUCTURES
MODULE 4: PYTHON FUNCTIONS
MODULE 5: PYTHON NUMPY PACKAGE
MODULE 6: PYTHON PANDAS PACKAGE
MODULE 1: DATA SCIENCE ESSENTIALS
MODULE 2: DATA ENGINEERING FOUNDATION
MODULE 3: PYTHON FOR DATA ANALYSIS
MODULE 4: VISUALIZATION WITH PYTHON
MODULE 5: STATISTICS
MODULE 6: MACHINE LEARNING INTRODUCTION
MODULE 1: COMPARISION AND CORRELATION ANALYSIS
MODULE 2: VARIANCE AND FREQUENCY ANALYSIS
MODULE 3: RANKING ANALYSIS
MODULE 4: BREAK EVEN ANALYSIS
MODULE 5: PARETO (80/20 RULE) ANALSYSIS
MODULE 6: Time Series and Trend Analysis
MODULE 7: DATA ANALYSIS BUSINESS REPORTING
MODULE 1: DATA ANALYTICS FOUNDATION
MODULE 2: OPTIMIZATION MODELS
MODULE 3: PREDICTIVE ANALYTICS WITH REGRESSION
MODULE 4: DECISION MODELING
MODULE 1: MACHINE LEARNING INTRODUCTION
MODULE 2: ML ALGO: LINEAR REGRESSSION
MODULE 3: ML ALGO: LOGISTIC REGRESSION
MODULE 4: ML ALGO: KNN
MODULE 5: ML ALGO: K MEANS CLUSTERING
MODULE 6: ML ALGO: DECISION TREE
MODULE 7: ML ALGO: SUPPORT VECTOR MACHINE (SVM)
MODULE 8: ARTIFICIAL NEURAL NETWORK (ANN)
MODULE 9: PROJECT: PREDICTIVE ANALYTICS WITH ML
MODULE 1: GIT INTRODUCTION
MODULE 2: GIT REPOSITORY and GitHub
MODULE 3: COMMITS, PULL, FETCH AND PUSH
MODULE 4: TAGGING, BRANCHING AND MERGING
MODULE 5: UNDOING CHANGES
MODULE 6: GIT WITH GITHUB AND BITBUCKET
Live Virtual
Instructor Led Live Online- Google Certification Preparation
- 4-Month | 200+ Learning Hours
- 20 HOURS LEARNING A WEEK
- 10 Capstone & 1 Client Project
- 365 Days Flexi Pass + Cloud Lab
- Internship + Job Assistance
Corporate Training
Customize Your Training- Instructor-Led & Self-Paced training
- Customized Learning Options
- Industry Expert Trainers
- Case Study Approach
- Enterprise Grade Learning
- 24*7 Cloud Lab