Shweta Vishwakarma

Shweta Vishwakarma

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AI Enabled Data Analyst |PCAP Certified | Transforming Data into Insights with Python & BI Tools| Machine Learning Enthusiast | Omdena Contributor
Noida, Uttar Pradesh, India
Contact Shweta regarding: 
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Full-time jobs
Starting at INR400k/year ~USD4.21k/year
Flexible work
Starting at INR300/hour ~USD3.16/hour
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Résumé

Jobs verified_user 0% verified
  • Brainwave Matrix Solutions
    Intern
    Brainwave Matrix Solutions
    Nov 2024 - Dec 2024 (2 months)
  • Omdena
    Junior ML Engineer
    Omdena
    Aug 2024 - Current (1 year 11 months)
  • Unified Mentor Private Limited
    Data Analyst
    Unified Mentor Private Limited
    Jun 2024 - Aug 2024 (3 months)
  • Unified Mentor Private Limited
    Intern
    Unified Mentor Private Limited
    Jun 2024 - Aug 2024 (3 months)
  • S
    Trainee
    Soft pro
    May 2024 - Jun 2024 (2 months)
    Gained in-depth knowledge and hands-on experience in advanced Python and machine learning algorithms. My expertise includes: Advanced Python Programming: Mastered advanced concepts such as object-oriented programming, decorators, and multithreading, enabling efficient and scalable data processing. Data Manipulation and Analysis: Utilized libraries like Pandas, NumPy, and SciPy for data cleaning, manipulation, and exploratory data analysis (EDA) with large datasets. Machine Learning Algorithms: Implemented various supervised and unsupervised learning models, including linear regression, logistic regression, and decision trees. Linear Regression: Specialized in developing and interpreting linear regression models for real-world applications s
  • accenture
    Data Analyst Trainee
    accenture
    Sep 2023 - Nov 2023 (3 months)
    Data Analyst Training by Centum Completed comprehensive training in data analysis, acquiring practical skills in various tools and techniques. Proficient in: SQL: Efficient database querying and management. Excel: Advanced data manipulation and analysis. Python, Pandas, and NumPy: Efficient data processing and handling. Matplotlib and Seaborn: Data visualization for insightful analysis. Tableau and R: Creating interactive dashboards and performing statistical analysis. Soft Skills: Enhanced communication, problem-solving, and teamwork abilities. This training has equipped me with a strong foundation to analyze data and provide actionable insights for business decisions.
  • accenture
    Data Analyst Trainee
    accenture
    Sep 2023 - Nov 2023 (3 months)
    Data Analyst Training by Centum Completed comprehensive training in data analysis, acquiring practical skills in various tools and techniques. Proficient in: SQL: Efficient database querying and management. Excel: Advanced data manipulation and analysis. Python, Pandas, and NumPy: Efficient data processing and handling. Matplotlib and Seaborn: Data visualization for insightful analysis. Tableau and R: Creating interactive dashboards and performing statistical analysis. Soft Skills: Enhanced communication, problem-solving, and teamwork abilities. This training has equipped me with a strong foundation to analyze data and provide actionable insights for business decisions.
Education verified_user 0% verified
  • J
    BCA, COMPUTER AND INFORMATION SCIENCES AND SUPPORT SERVICES
    JNMCollege For Advance Studies and Technology Khushahal Nagar BadalalpurVaranasi
    Jan 2018 - Dec 2021 (4 years)
Projects (professional or personal) verified_user 0% verified
  • V
    Vehicle Routing Optimization (CVRP)
    Oct 2025 - Dec 2025 (3 months)
  • C
    Market Reasearch for Air purifier
    Codebasics Bootcamp
    Mar 2025 - May 2025 (3 months)
  • D
    Inventory Management & Reorder Optimization
    Data DNA
    Feb 2025 - Mar 2025 (2 months)
    • Analyzed 5,000+ SKU records to identify demand trends and stock inefficiencies. • Built automated reorder logic and inventory health dashboards. • Supported cost control by identifying slow-moving and overstocked inventory.
  • Y
    YouTube Analysis Project
    Aug 2024
    Objective: The YouTube Analysis project aims to examine data from YouTube videos to uncover insights into video performance, viewer engagement, and content trends. The goal is to optimize content strategy, enhance viewer engagement, and improve overall channel performance. Data Overview: Dataset: The dataset includes metrics and attributes related to YouTube videos, such as views, likes, comments, and other engagement metrics. Key Columns: Video ID, Video Title, Upload Date, Views, Likes, Dislikes, Comments, Video Length, Category, Tags, and Channel Name. Key Insights Highest Subscribers: T-Series with 170M subscribers (Music)1. Lowest Subscribers: Justin Bieber with 76M subscribers (Music)3. Top 3 Channels: T-Series: 170M subscribers (Musi
  • C
    Crop Production Analysis
    Jul 2024 - Aug 2024 (2 months)
    The Crop Production Analysis project aims to explore and analyze crop production data to identify trends, patterns, and insights related to crop yields and agricultural performance. The goal is to provide actionable recommendations to optimize crop production strategies, improve resource allocation, and support decision-making in agriculture. Data Overview: Dataset: The dataset includes information on crop production across various states and districts, covering different crop types and seasons. Key Columns: State_Name, District_Name, Crop_Year, Season, Crop, Area, Production. Focus Areas: Different crops, seasonal variations, yield patterns across states and districts.
  • B
    Birds Strike Analysis
    Jul 2024 - Aug 2024 (2 months)
    The Bird Strike Analysis project aims to investigate and understand bird strike incidents involving aircraft. The goal is to identify patterns and trends in bird strikes, assess their impact on flight safety, and provide actionable insights to mitigate risks and improve aviation safety measures. Data Overview: Dataset: The dataset contains records of bird strike incidents, including various attributes related to the aircraft, wildlife involved, and the circumstances of each incident. Key Columns: Record ID, Aircraft Type, Airport Name, Altitude Bin, Aircraft Make/Model, Wildlife Number Struck, Wildlife Number Struck Actual, Effect Impact to Flight, Flight Date, Effect Indicated Damage, Number of Engines, Airline/Operator, Origin State, Phas
  • A
    Amazon Sales Analysis
    Jun 2024 - Jul 2024 (2 months)
    The Amazon Sales Analysis project aims to evaluate and understand sales data from Amazon to uncover key insights into sales performance, customer behavior, and product trends. The goal is to optimize marketing strategies, improve inventory management, and enhance overall sales performance. Here are some key insights of the Amazon Sales Analysis: Total Revenue: $137.35 million Units Sold: 512,871 Average Unit Price: $276.76 Total Profit: $44.17 million Top Products by Profit Margin: Clothes: 57.47%1 Cereal: 50.82%2 Vegetables: 49.78% Sales Channels: Offline: 57.6% of total revenue3 Online: 42.4% of total revenue Regional Sales Performance:4 Highest Sales: East Region Lowest Sales: South Region Country with Highest Profit: Djibouti ($2.5 mil
  • P
    Pizza Sales Analysis
    Oct 2023 - Nov 2023 (2 months)
    The Pizza Sales Analysis project aims to explore and understand sales data related to pizza products. The goal is to identify key sales trends, customer preferences, and product performance to inform business strategies, optimize inventory, and enhance marketing efforts. Here are the key insights from the Pizza Sales Analysis project: Age Group: The 18-25 age group is the highest spender, accounting for 40% of total sales. Gender: Males spend slightly more than females, contributing to 52% of total sales. Time of Day: Evening hours (6 PM - 9 PM) see the highest sales, making up 45% of daily sales. Day of the Week: Fridays and Saturdays are the peak days, with 30% of weekly sales occurring on these two days. Popular Toppings: Pepperoni and
  • D
    Diwali Sales Analysis
    The Diwali Sales Analysis project aims to examine sales data during the Diwali festival to identify key trends, customer behavior, and product performance. The goal is to derive actionable insights that can help optimize marketing strategies, inventory management, and promotional efforts for future Diwali seasons Here are the key insights from the Diwali Sales Analysis project: Age Group: The 26-35 age group spends the most, accounting for 35% of total sales. Gender: Females spend more than males, contributing to 55% of total sales. Occupation: People in the IT sector are the highest spenders, making up 40% of total sales. State: Uttar Pradesh leads in spending, with 20% of total sales. Product Category: Clothing & Apparel are the top-selli
  • V
    Vrinda Store Analysis
    Key Insights Orders Via States: Bar chart showing orders ranging from approximately 3,000 to 9,000 across different states. Store Status: Pie chart indicating 80% of orders were delivered, 10% returned, and 10% canceled. Customer Demographics: Pie chart showing a larger portion of women customers compared to men. Sales Distribution: Horizontal bar graph highlighting the top 5 states by sales, and a pie chart showing 35% of orders came from online channels.
  • A
    AtliQ Motors Analysis